Thermal generation

Thermal generators are modelled using short run marginal costs that reflect the variable cost of generating electricity. These SRMCs are calculated by multiplying each plant’s heat rate (a measure of thermal efficiency, typically in GJ/MWh) by relevant fuel commodity prices - such as that of gas or coal. Where applicable, variable operating and maintenance costs may also be included to reflect a more complete cost of dispatch.

In the NEM, while generators bid based on their SRMC, the NEM dispatch engine (NEMDE) accounts for network losses through Marginal Loss Factors (MLFs). Rather than adjusting the bid bands upon bidding in on the generator’s side, the NEM’s dispatch algorithm divides each generator’s bid price by its MLF to determine an effective cost at the Regional Reference Node (RRN). This means that, all else being equal, generators with lower MLFs (i.e., located further from the load or subject to higher losses) are less competitive in the dispatch process.

To reflect this behaviour, the model approximates the impact of MLFs by dividing each generator’s calculated SRMC by its MLF. This increases the apparent cost of generation for units with lower MLFs, ensuring that the model prioritises generation in locations with lower transmission losses - mirroring how NEMDE accounts for locational efficiency.

This adjustment is particularly important for modelling the merit-order dispatch, as it can shift which generators are selected under competitive market conditions. It also captures one of the key spatial dynamics of the NEM, where generators located in remote renewable zones or areas with constrained transmission infrastructure may face commercial disadvantages despite having low raw SRMCs.

In summary, SRMCs in the model are derived from fuel efficiency and price fundamentals, and then adjusted for locational effects using MLFs. This replicates the practical outcome of the NEM dispatch process, where energy is scheduled based not just on cost, but on the delivered value of that energy at the regional node after accounting for losses.