We design our models to provide the most accurate and complete answer given the realities of the marketplace.

In development, we deploy insightful techniques, adopt the world’s best practice, and focus on five core modelling principles.

  • Independence
    We build our own power and commodities models, rather than relying on black box third-party models, resulting in greater analytical rigour and objectivity. As we own the code, models can be easily calibrated to each individual market
  • Transparency and Flexibility
    Results can be easily traced back to the underlying assumptions and data. Clients can flex any assumption to reflect their market views, crucial to giving investment committees confidence in various outcomes under different scenarios
  • Consistency
    We integrate major markets to produce fully consistent market outcomes and reflect the potential dispatch of assets. This is increasingly important as power markets integrate and harmonise
  • State-of-the-art
    Our large team of market experts keep the models updated with the latest features and market developments
  • Proven Performance
    Our models must be capable of reproducing important historical time series with a high degree of accuracy

Energy system model (AER-ES)

AER-ES is our in-house large scale power market model forecasting prices, plant dispatch, and capacity decisions up to 2050 and beyond. Used to accurately model a variety of markets, including all the major interconnected power markets in Europe, and the Australian NEM. We model all the major power plants in a system, with a wide range of possible input specifications for each generator and market, across all the key technologies.

What sets AER-ES apart from other energy market models is our fully integrated approach. Our model optimises across interconnected half-hourly power market dispatch and capacity decisions simultaneously, so market entry and exit are driven and fully consistent with dispatch. We are experienced in forecasting capacity markets, endogenously modelling long term contracts, and considering plant and revenue specific discount rates. Our approach has been used to accurately forecast capacity auctions in many countries such as GB, France, and Poland.

Further to this, we recognise the importance of capturing the complex interaction between a growing intermittent supply and flexible demand. In addition to our modelling of both smart elastic and inelastic EVs and other behind the meter technologies, we have incorporated hydrogen markets into our power modelling. This considers the interactions between electrolysers, RES generation, other sources of hydrogen generation such as SMR, as well as hydrogen consumption for power. By fully integrating the key aspects of power markets, we provide the necessary tools to model evolving power markets through the energy transition.

Global general equilibrium model (AER-GLO)

Our global general equilibrium model provides a long-term view on fuel prices, production, and consumption by region.

The model is the first of its kind, linking a global general equilibrium energy model (developed by building on the widely-used GTAP database) with a high-resolution resource extraction algorithm based on a cost-minimisation solver algorithm.

The model acknowledges the substantial potential for inter-fuel substitution, as well as interactions with the global economy rather than treating non-energy sectors as exogenous model inputs. It includes detailed modelling of sectoral and economy-wide energy demand with a special focus on energy intensive industries.

Such a modelling framework is crucial to guarantee internally consistent scenarios. Several energy majors have already commissioned us to help develop holistic multi-fuel long-term outlooks, across several scenarios, based on the model’s capabilities.

Global gas market model (AER-GAS)

Our global gas dispatch model contains an unprecedented level of detail on global infrastructure providing long-term projections for the global gas markets.

We draw from our in-house suite of models for full consistency throughout our outlooks. We combine the capabilities of our general equilibrium model and electricity market modelling platforms to provide global projections for supply and demand, including a detailed view on gas-for-power, to support our gas model. This enables us to capture the complex interactions between energy markets and the global economy, as well as substitutions between different fuels.

Within our global gas market model, we represent the complexity of gas markets with economic accuracy through sophisticated modelling. Our modelling reconciles short-term market behaviour, such as infra-annual supply flexibility, with long-term economics, such as investments in capacity additions.

In Europe, we model the entire transport pipeline network, gas storage facilities, interconnectors, LNG terminal and gas extraction nodes to understand physical constraints and bottlenecks.

The global LNG market is modelled in detail. We geocode every liquefaction and regasification terminal and simulate the behaviour of the entire fleet of LNG carriers.

Consequently, the global gas market model provides a wide range of outputs, including prices, flows and assets performance, with high granularity. These results underpin our quarterly outlook on European gas markets, but also inform our studies on global gas markets, valuations of infrastructure assets, strategic analysis, security of supply stress-tests, market design assessments, and others.

Electricity network model (AER-EN)

Our electricity network model (AER-EN) is fully integrated with our electricity market model AER-ES and models the flows in the network in detail. While building on top of the current network, future network augmentations are considered as well as capacity retirement, capacity expansion and the generation mix as direct inputs from the AER-ES model. The network model then solves for the flows and losses on the individual lines of the network which can be analysed for various applications such as network congestion, N-1 contingency analysis or the impact of individual generators on overloaded lines.

Among other applications the network model is used to forecast marginal loss factors (MLFs) in the Australian market. Here we consider the Network Integrated System Plan (ISP) for future network augmentations, industrial load and connection point load forecasts, the future capacity and generation mix from AER-ES and follows AEMO’s forward looking loss factor methodology. On the other hand, our market model AER-ES incorporates indicative MLFs into its capacity and dispatch decisions which are informed by the network model. With this integration of AER-ES and AER-EN we can capture the impact of market scenarios and their resulting capacity and generation mixes on MLFs and vice versa.

Asset dispatch suite (AER-AD)

Our power asset valuation models use in-house algorithms to simulate asset dispatch across multiple markets for a wide range of technologies against prices generated by our power market model.

Our algorithms take market prices, operational costs, technical and regulatory constraints, as well as other incentives such as embedded benefits, and produce a realistic and granular (typically hourly or half-hourly) dispatch profile, from which forecasts of various revenue and cost streams are derived. In order to ensure that our dispatch outcomes are realistic, our algorithms are regularly calibrated against historical data and are able to take into account real-world factors such as a lack of perfect foresight of future prices. Furthermore, these tools are highly flexible and can be customised to capture detailed asset-specific incentives, constraints and/or operational strategies. This flexibility means that we can produce realistic dispatch behaviour and revenue forecasts not just for generic assets but for a specific asset or combination of assets in question.