G2M2 Wiki

The purpose of a gas storage plan is to provide G2M2 with reasonable assumptions for the range of possible storage levels for the end of each period for each modeled facility. In the databases being designed at this time (Q1 2022) we are modeling gas storage at the facility level for three countries (United States, Canada, and China) and all other areas at the level of the geo-political unit (GPU). Currently we have two major data sources for storage data on monthly level – JODI gas database and AGSI. JODI gas data base reports 36 countries for month-end levels and AGSI reports 22 countries for the similar data. We use GPCM for storage plan analysis for the U.S. and Canada, and then leaves rest of the countries using either JODI or AGSI data.

Figure 1: Historical Storage Levels in MCM for Austria (source: JODIGAS).

All the historical storage data is stored and updated in the table <Storage Historical Data>.

Using this data, we can identify an average historical storage level for each month-of-year of a multiple year storage level history.

Figure 2: Five-Year Average Austrian Storage Levels by Month-of-Year (MCM)

Postulating this to be the long-run storage plan, we can combine it with history to get the following:

Figure 3: Combined Historical and Forecast Storage Levels (MCM)

Note the gap or “Forecast Error” for the last data point (Jul-2019). The historical (blue) and forecast (red) points for Jul-2019 are separated by almost 2,500 MCM. In order to use the average values as a forecast for future storage levels, we need to merge the two series in a more gradual fashion over several years, such as the following:

Figure 4:  Merged Historical and Long-Run Future Storage Plan (MCM).  Blue is Historical, Red is Long-Term Average, Green is the “Bridge” between the two series.

The procedure for creating or updating a storage plan for which we have JODIGAS data is:

1. Acquire the historical storage levels and confirm that there are no gaps in the data over the past several years.
2. Calculate the average level for each month-of-year over the last several years. The number of years is a parameter to be determined by the user. In the example above, we used 5 years.
3. Compute the “bridge” levels between the historical and the long-term average storage by month-of-year, where the length of the “bridge” is a parameter selected by the user.
4. The easiest way of doing this is to assume that the difference between the bridge value and the historical value for the last month of known data declines regularly for each month into the future. For example, in Figure 4, we decreased the “error” between the bridge and the long-run average from its initial value of 2,374 (in Jul-2019) by 50 per month until the two series converged in Jul-2023. We used a 4-year period for the “bridge”.

Note that the Gas Storage Plan for each facility has two parameters for each period: MinQty and MaxQty. All of the discussion above concerns the MinQty. The MaxQty is typically selected to be a certain percentage higher than the MinQty. For our work we usually select 20% so MaxQty=1.2*MinQty. However, when computing a Gas Storage Plan, we do have historical values, so for all of those, we make MaxQty = MinQty.

When there is drastic change in demand profile for a country in the future, G2M2 storage plan change accordingly.

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