Integrated Development of Low-Carbon Energy Systems (IDLES): A Whole-System Paradigm for Creating a National Strategy

能源系统的长期演变是由许多行为者的投资决策决定的，这些行为者包括上游资源公司、发电厂运营商、网络基础设施提供商、车辆所有者、运输系统运营商以及建筑开发商和占有者。但这些决定是由地方和国家政府为实现能源、空气质量、经济增长等政策目标而设计的市场和激励措施故意塑造的。因此，很明显，政府和企业需要详细和可靠的证据，以证明我们可以实现什么，我们应该瞄准什么形式的能源系统，需要鼓励哪些新技术，以及能源系统如何成为新产品和服务的产业战略的一部分。人们普遍认为，需要一种全系统的能源观，不仅包括多个能源部门(天然气、热力、电力和运输燃料)，而且还包括个人和组织在能源消耗部门的行为，如交通和建筑环境。这意味着，在一个未来的综合系统中对能源的生产、输送和使用进行建模是非常复杂的，在分析上也是具有挑战性的。为了向政府和企业提供证据，证明优化后的未来系统可能是什么样子，人们必须迎接这些建模挑战。仅就电力系统而言，就有一些既定的模型可以在某些假设(和敏感性)的情况下优化安全、成本和排放，这些模型已被用于提供政策和商业战略证据。然而，这样的模型不存在于集成系统的复杂交互作用中，也不存在于揭示特别困难的操作条件所需的详细程度上。我们的愿景是通过将多物理优化技术经济模型与人类行为的机器学习以及新兴的多载波网络和转换技术相结合，来解决综合能源系统所需的非常具有挑战性的建模问题。我们希望采取的方向是明确的，但在此过程中还有许多具体的挑战，需要高度创新的解决办法来克服遇到的障碍。方案赠款结构使我们能够组建一支横跨多个学科的杰出专家团队。例如，有新的令人兴奋的机会，可以应用机器学习，以定量的方式识别消费者行为的模型，以及对激励措施的反应，这些激励措施可以帮助探索综合能源体系中需求侧的灵活性。我们邀请了来自能源系统互补部门的四个主要合作伙伴，他们将为该方案提供大量资金(大约35%的额外资金)，更重要的是，我们和彼此都参与进来，分享见解、挑战、数据和案例研究。EDF Energy提供了能源零售业务的视角，并提供了对智能电表跟踪数据的访问。壳牌提供了对未来将用于交通和建筑服务的燃料的见解。国家电网(系统运营商)提出了利用灵活性和新的服务主张来实现系统高效运营的观点。ABB是数据采集和控制系统的供应商，提供分散控制的行业视角。ABB已承诺提供大量设备和资源，以建立分散控制的验证和演示设施。我们也在吸引新进入者的例子，他们通常是拥有潜在颠覆性技术和商业模式的较小公司，他们将参与并分享他们的一些见解。

The long-term evolution of energy systems is set by the investment decisions of very many actors such as up-stream resource companies, power plant operators, network infrastructure providers, vehicle owners, transport system operators and building developers and occupiers. But these decisions are deliberately shaped by markets and incentives that have been designed by local and national governments to achieve policy objectives on energy, air-quality, economic growth and so on. It is clear then that government and businesses need detailed and dependable evidence of what can be achieved, what format of energy system we should aim for, what new technologies need to be encouraged, and how energy systems can form part of an industrial strategy to new goods and services. It is widely accepted that a whole-system view of energy is needed, covering not only multiple energy sectors (gas, heat, electricity and transport fuel) but also the behaviour of individuals and organisations within the energy consuming sectors such as transport and the built environment. This means that modelling energy production, delivery and use in a future integrated system is highly complex and analytically challenging. To provide evidence to government and business on what an optimised future system may look like, one has to rise to these modelling challenges. For electricity systems alone, there are established models that can optimise for security, cost and emissions given some assumptions (and sensitivities) and these have been used to provide policy and business strategy evidence. However, such models do not exist for the complex interactions of integrated systems and not at the level of fine detailed needed to expose particularly difficult operating conditions. Our vision is to tackle the very challenging modelling required for integrated energy systems by combining multi-physics optimising techno-economic models with machine learning of human behaviour and operational models emerging multi-carrier network and conversion technologies. The direction we wish to take is clear but there are many detailed challenges along the way for which highly innovative solutions will be needed to overcome the hurdles encountered. The programme grant structure enables us to assemble an exceptional team of experts across many disciplines. There are new and exciting opportunities, for instance, to apply machine learning to identify in a quantitative way models of consumer behaviour and responsiveness to incentives that can help explore demand-side flexibility within an integrated energy system. We have engaged four major partners from complementary sectors of the energy system that will support the programme with significant funding (approximately 35% additional funding) and more importantly engage with us and each other to share insights, challenges, data and case studies. EDF Energy provide the perspective on an energy retail business and access to smart meter trail data. Shell provide insights into the future fuels to be used in transport and building services. National Grid (System Operator) give the perspective of the use of flexibility and new service propositions for efficient system operations. ABB are a provider of data acquisition and control systems and provide industrial perspective of decentralisation of control. ABB have committed to providing substantial equipment and resource to build a verification and demonstration facility for decentralised control. We are also engaging examples of the new entrants, often smaller companies with potentially disruptive technologies and business models, who will engage and share some of their insights.