Frontier’s proprietary modelling tools are state of the art and help our clients evaluate energy policies and regulations, support arbitration and disputes, and navigate complex business decisions.
Our models are regularly employed in policy analysis, price forecasting, commercial asset valuation, dispute resolution, and evaluating the impacts of energy policies, including capacity markets and renewable support mechanisms.
Our team of expert energy market modellers and data scientists can easily adapt our models to add project-specific functionality, or develop entirely bespoke models. Our model portfolio includes:
COMET: Cross-Sector Optimisation Model for the Energy Transition
COMET provides policymakers, system planners, and investors with critical insights into the design of tomorrow’s decarbonised energy system. Covering electricity, gases (methane and hydrogen), liquids, biofuels, and emerging energy carriers, COMET evaluates the infrastructure, technologies, and supply pathways required to build an affordable, efficient, and resilient energy system across Europe through 2050 and beyond.
Learn more about COMET and how we have used it for our clients on our dedicated site
SPIRIT: Highly granular unit dispatch model
Alone or in combination with COMET, our SPIRIT model is used to analyse dispatch of individual generation and storage units with highly detailed technical properties. Using hourly energy prices as input, the model optimises operation to maximise profits. The results provide crucial insights for long-term investment and divestment decisions. Unlike off-the-shelf models, Frontier has complete access to the source code of SPIRIT, making it especially valuable for disputes where it is vital to understand what is driving every result.
HyLO: Hydrogen cost modelling
HyLO is our optimisation model for forecasting levelised costs of hydrogen (LCOH) under realistic scenarios. It accounts for demand profiles, infrastructure, renewables, and financing. Whether for constant industrial use or variable power plant needs, HyLO finds the optimal system setup – from production to transport – based on techno-economic parameters. This enables reliable cost estimates tailored to local energy profiles and hydrogen delivery requirements.
Click here to read a detailed example of our work in this sector.
Gas flow modelling
We have a long track record of modelling gas flows in the European gas market. Our modelling framework can be applied to any interconnected gas infrastructures worldwide. We frequently use our model in combination with our database of European gas infrastructure at a market area / transmission system operator (TSO) level. The model provides insight into the operation and utilisation of gas infrastructure, including potential future bottlenecks and security of supply indicators.
Customer behaviour modelling
We combine behavioural economic and data science to produce models of how customers behave. By using techniques such as Agent Based Modelling (ABM) and causal machine learning, our models help clients understand the fundamental drivers of policies and business models, rather than acting as “black boxes”. Our ABMs have been used to simulate the uptake and usage of low-carbon heating and transport solutions and can be combined with customer archetypes to understand the distributional impacts of different pathways to decarbonisation. Our econometric propensity models help utilities unpick the marketing channels which are best suited to encouraging different groups of customers to take up technologies like smart meters.
Read about the use of agent-based modelling for simulating heating system take-up
Read about our distributional model used by the UK’s Climate Change Committee