Energy models

Energy markets are influenced by their design, by market structure, by regulations and government policies, by consumer behaviour, and by unexpected events like plant breakdowns. This complexity means it is difficult to predict outcomes in energy markets, especially into the longer term.

This is compounded as Governments seek to influence markets to achieve environmental outcomes or to address concerns about security and reliability or high prices. Frontier Economics has been involved in the design, reform and regulation of energy markets globally, and has provided advice on investments, transactions and strategy.

From this work, we have developed a sophisticated suite of in-house modelling and analytical tools that combine robust economic frameworks, direct experience in numerous energy markets, best practice software design and extensive sources of data accrued over decades of analysing energy markets around the world. These models have evolved over time in response to the ever-more complex questions facing our clients.

Our energy models

whirlygig calculates the least-cost mix of existing and new generation to meet demand over time by optimising total generation costs in the market. whirlygig is most often used to inform decisions on the future long run marginal cost in an electricity market.

spark produces sustainable, robust patterns of generator bidding behaviour by combining a least-cost electricity dispatch engine with game theory. spark ensures market price forecasts account for the likely behaviour of generators when faced with real world scenarios, such as extreme weather events.

sync models each sequential dispatch interval, accounting for the short-term expectations about future supply and demand that drive decisions about the charging and discharging of batteries and the operation of pumped-storage hydro plant.

strike determines an efficient mix of energy purchasing instruments from a suite of options (spot, physical and financial) for a range of risk levels using portfolio theory. It provides a framework in which the trade off between risk and reward for a given business can be explicitly measured.

switch examines the payoffs to customers from changes in tariff structures or decisions to install solar PV, batteries of other distributed energy resources.

whirlygas examines the longer-term effects of changes in competitive gas markets such as the least-cost operation and investment in a domestic or international gas market over a long-term investment horizon. It is often used to inform assumptions about gas input prices for electricity generation.

Our analytics team also regularly assists our clients develop bespoke models or audit internal models. This can include building block models, pricing models, financial models or optimisation models to inform contracting decisions.

Super models

Over the past 15 years our models have been used for many different purposes, often under a great deal of regulatory, commercial or legal scrutiny.

Our work includes:

  • informing the level at which the regulated retail price should be set in a number of jurisdictions
  • determining the potential costs and benefits of different proposed adjustments to the Renewable Energy Target
  • forecasting market prices to support due diligence by potential purchasers of electricity market assets
  • analysing potential market behaviour to determine the effects of different generator ownership assumptions on market competitiveness
  • assessing the value of specific transmission augmentation proposals to the market.

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