Natural Gas Consumption

Thermoelectric Demand

The thermoelectric demand for natural gas depends on the dispatch frequency of the gas-fired thermal plants. This dispatch in turn, depends on the operation politics of the electrical system, which is a function of a series of other factors such as the hydrological situation and the offer-demand balance of the electric system.

Thus, its forecast is obtained based on the simulations of the hydrothermal dispatch to meet load, using hydrothermal dispatch models for the operation of the system. EPE uses the Newave energy optimization model, developed by CEPEL. The system operation policy resulting from the model is simulated considering several scenarios of affluent natural energies, thus estimating the thermoelectric generation for each of these scenarios in each plant that composes the SIN configuration, already in operation or expanding along the planning period.

The estimation of the consumption of natural gas is then obtained from statistics constructed from the sample of results obtained.

Non-thermoelectric demand

The projection of the non-thermoelectric demand for natural gas involves a process that starts from the data obtained from research carried out by EPE on the demand perspectives for the next ten years, through the Natural Gas Market Information System (INFOGAS). This system was developed by EPE for the purpose of collecting and storing data, through which natural gas distribution companies and industrial consumers provide natural gas demand information on an annual basis.

The forecast exercise is inserted in an integrated view of energy demand, in which a critical analysis of the data reported by the agents combined with the use of total energy demand forecast models is performed, which ensures consistency with the economic and energy scenarios used by the EPE in their studies. This evolution of natural gas demand, in turn, is established from the study of long-term scenarios in which the main boundary conditions are set.

Beyond the long-term determinants, the studies incorporate other determinants like the industry current outlook, as well as medium-term definitions and strategies, which may influence relevant parameters in the forecast horizon.

Finally, the consistency analysis takes into account different degrees of competitiveness compared to the main substitute energy resources, mainly in industry. This allows the sum of individual markets for each energy resource to be consistent with estimated total demand.