Novel Agent-based Approaches for UK Whole Energy Systems Modelling for UK Net-zero Emissions by 2050, with a Focus on Hydrogen Integration

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Based on the recommendations from the Climate Change Committee (CCC) outlined in the UK's Sixth Carbon Budget, the UK submitted its Nationally Determined Contribution (NDC) to the United Nations Framework Convention on Climate Change (UNFCCC) on 'reducing economy-wide greenhouse gas emissions by at least 68% by 2030, compared to 1990 levels' Department for Business, Energy & Industrial Strategy, 2022). Along with this recommendation, the CCC reflected upon key lessons in their recent insights report (Climate ChangeCommittee, 2023); these include emphasis on the need for sector-level analysis, whole-system optimisation models and scenario analysis which inform important decision-making which facilitates the pathway to Net Zero Emissions (NZE) by 2050.Development and adoption of low-carbon technologies are key to cutting down emissions, consequently their implementation has been laid out in the planning of many countries' net zero pathways. Of these technologies, there has been a rising interest in hydrogen for alternative applications in the power, gas and transport sectors due to its potential as a fuel and storage vector. Having a high gravimetric energy density of 120kJ/g, hydrogen can serve as an efficient fuel for varied uses for example in power generation as well as blending hydrogen gas into natural gas networks for residential and commercial heating (IEA, 2019). The UK has detailed a Hydrogen Strategy to meet the 5GW production target by 2030 in line with the Sixth Carbon Budget (Department for Business, Energy & Industrial Strategy, 2021). Therefore, it is important to consider the integration of hydrogen within the understanding and modelling of the UK energy system.MUSE (ModUlar energy systems Simulation Environment) is a novel open-source AGM environment which can be used to answer many questions relating to changes in a user-modelled energy system over a time (Giarola et al., 2022). MUSE allows the user to model multiple sectors and their respective technologies, commodities and end-use demands within input files which drive the decisions made by the model. Results regarding investment decisions of different agents interacting with the modelled energy system can be sought by the user; these investment decisions are computed on the point of view of the agents (e.g. investors and consumers) and their preferred investment strategies. This serves as a key advantage of MUSE as most models which are based on cost minimisation may offer decisions based on lowest cost which may not be the only investment strategy for different agents interacting within an energy system; for example agents who are more keen to adopt newer technologies in order to reduce their carbon footprint may be less stringent on cost minimisation than those who have a more traditional approach to investment. Another key strength of MUSE is that it assumes that the agents have limited foresight in changes in the energy system as the user can define the number of years in which agents have knowledge of projected prices and demand. These characteristics allow the user to model the system as close to real-life as possible.With the ambitious targets set by the UK government to meet net-zero emissions, whole energy system modelling, covering a variety of sectors within the energy supply chain, will play a crucial role in answering key questions relating to the different pathways to net zero and relevant decision-making. The development of a hydrogen economy in the UK also has many implications within a range of sectors, therefore it is key to investigate its integration into the UK energy system.