G2M2 Wiki

In the text below, a very similar methodology is presented describing how G2M2, RBAC’s Market Simulator for Global Gas and LNG, computes global gas forecasts of prices and flows.

G2M2 is a model of the increasingly integrated global market for gas and LNG. It is a network model consisting of points where gas is produced, bought and sold, stored, and consumed. These points are called “nodes” in a network model. And it consists of paths through these various points representing the pipeline grid which delivers gas from producing areas to consumers. Each point-to-point component of a path in a network model is called an “arc”.

Some of these nodes represent terminals where LNG is produced and exported in LNG tankers or where it is received and converted back to gas. The arcs between these terminals represent paths for LNG tankers from origin to destination.

The question which G2M2 answers is: given a set of assumptions about supply in producing areas and demand in consuming areas, plus knowledge about the capacity and cost of transportation and storage, what set of prices at the nodes and flows on the arcs would be consistent with a relatively free and competitive market for gas?

G2M2 calculates this answer using the basic principles of equilibrium economics. Supply and demand must be in balance. This balance must exist at every node. A balance, or equilibrium, occurs when the price differential between any two points in the network equals the cost of moving gas between those two points and, therefore, there is no reason to increase or decrease the amount of gas flowing between the two points.

At supply points, this means there is no reason to increase (or decrease) production since the amount produced is equal to the amount demanded at that price. At demand points, there is also no reason to increase (or decrease) the amount of gas demanded, because supply and demand are in balance at the market price there.

G2M2 uses a step-by-step, iterative method to compute this equilibrium solution. It starts with a trial “solution” which has no gas flowing in the network. From this beginning point, it scans through the various possible supplies, demands, and pathways from supply points to demand points, and finds the one which has the greatest price / cost differential. It then creates a new trial “solution”, flowing the maximum amount it can from a low-cost producer along a low-cost pathway to a customer group (sector) which, based on its demand curve, is willing to pay a high price. At this early point in the solution process, prices are low at that supply point, high at the demand point, and at values in between at the various transportation points used to move gas from the supply to the demand point.

The algorithm then looks for another, similar situation where a profitable flow from producer to consumer can be made. At each iteration, G2M2 must compute an implied price at each point in the transportation network. As the capacity of each pathway is used up, the price of transportation along that path increases, reflecting the operation of supply and demand for transportation. As more gas is demanded at various supply points, higher cost producers can sell their gas and the price at these points goes up. As the customers willing to pay higher prices are satisfied, the market tries to satisfy those customers not willing to pay so much, and prices at the demand points come down.

G2M2 continues to look for opportunities to move gas from suppliers to consumers that have a “profit” associated with them. This is exactly analogous to the process that current day gas traders and marketers use to make money for their firms. If they find a way to move gas from one market point to another at a cost less than the price differential between those points, they will do so.

This process can also involve time. In other words, traders might want to buy gas at a certain location during one period of time, store it, and then sell it at the same or a different location at a later time. If the relative price between these two space-time locations is greater than the cost, then the trader will try to make the deal. G2M2 computes prices and flows over both space and time, including storage injections and withdrawals as well as production, pipeline transportation, and delivery to customers. Its algorithm uses the same “thought process” that traders and marketers use to conduct business in the competitive global market for natural gas and LNG.

The mathematicians who developed the algorithm that G2M2 uses have proved that it will always converge to a solution where the price and flow variables will be consistent with an “economic equilibrium”. This means that arbitrage opportunities will have been cleared and the system will be in balance at every location and time period.

Actually, price differentials between two points can be different from the cost of transportation (and / or storage) when the path between the points becomes “congested” and there is no more capacity to sell. In those instances, G2M2 would like to take advantage of the potential for additional “profit”, but there is not enough physical capacity to do so. This is, of course, very important information, because the solution reveals paths where additional capacity might be needed in the present or future. The difference between the price differential and the cost is a measure of the economic value of additional capacity between those two points.

G2M2 also considers contracts to buy liquefied natural gas at LNG export facilities or from portfolios of other market players and to deliver that LNG to destinations around the globe. Some of these contracts involve “destination restrictions” which constrain the buyer to deliver the gas to a specific location. Some are more flexible and allow the buyer to transport and deliver the LNG to the highest price market available. And some LNG can be purchased and delivered on a growing “spot market” based on fluctuating supply and demand conditions.

G2M2’s solutions should not be viewed as “crystal ball” forecasts. They are always based on a set of user-supplied assumptions about supply and demand, along with factual information about transportation and storage capacities and costs. The user should construct alternative scenarios with a variety of supply and demand assumptions in order to test out the sensitivity of the results to these assumptions. The user can construct scenarios involving capacity expansions of the pipeline and storage infrastructure in order to assess the impact of such capacity expansions as well as the degree to which the market may need and value that new capacity.

In summary, G2M2 is a market simulator which is useful for computing credible sets of flows and prices throughout the global natural gas and LNG delivery network over the user-specified time horizons. Each set of flows and prices will be consistent with the assumption that the global natural gas industry is a reasonably competitive, price-driven market, where there is a free flow of information about prices, supplies, and demands, and enough marketers and traders to create a relatively efficient market.

Please contact customer support if you have any further questions - RBAC, Inc. support line (281) 506-0588 ext. 125, from 9:00 am to 5:00 pm CT