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

根据英国第六次碳预算中概述的气候变化委员会（CCC）的建议，英国向联合国气候变化框架公约（UNFCCC）提交了国家自主贡献（NDC），即“到2030年将整个经济范围的温室气体排放量与1990年相比至少减少68%”。2022年）。沿着这一建议，气候变化协调委员会在其最近的见解报告中反思了主要经验教训（气候变化委员会，2023年）;其中包括强调需要进行部门一级的分析，全系统优化模型和情景分析，为重要决策提供信息，促进到2050年实现净零排放（NZE）。碳技术是减少排放的关键，因此，许多国家在规划净零排放路径时都规定了碳技术的实施。在这些技术中，由于氢作为燃料和储存载体的潜力，人们对氢在电力、天然气和运输部门的替代应用越来越感兴趣。氢具有120 kJ/g的高重量能量密度，可以作为各种用途的有效燃料，例如发电以及将氢气混合到天然气网络中用于住宅和商业供暖（IEA，2019）。英国已经详细制定了一项氢战略，以实现到2030年5GW的生产目标，这符合第六个碳预算（商业，能源和工业战略部，2021年）。因此，在理解和建模英国能源系统时考虑氢的集成是很重要的。MUSE（ModUlar能源系统模拟环境）是一种新型的开源AGM环境，可用于回答与用户建模的能源系统随时间变化有关的许多问题（Giarola等人，2022年）。MUSE允许用户在输入文件中对多个部门及其各自的技术、商品和最终用途需求进行建模，从而推动模型做出决策。用户可以寻求与建模的能源系统交互的不同代理的投资决策的结果;这些投资决策是根据代理（例如投资者和消费者）的观点及其偏好的投资策略来计算的。这是MUSE的一个关键优势，因为大多数基于成本最小化的模型可以提供基于最低成本的决策，这可能不是能源系统内不同代理商交互的唯一投资策略;例如，更热衷于采用新技术以减少碳足迹的代理商可能比那些采用更传统投资方法的代理商对成本最小化不那么严格。MUSE的另一个关键优势是，它假设代理人对能源系统变化的预见有限，因为用户可以定义代理人了解预计价格和需求的年数。随着英国政府制定了实现净零排放的宏伟目标，涵盖能源供应链中各个部门的整个能源系统建模将在回答与净零排放不同途径和相关决策相关的关键问题方面发挥至关重要的作用。英国氢经济的发展也对一系列行业产生了许多影响，因此，研究其融入英国能源系统是关键。

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.