System Transition to Digital Energy

这项研究的总体目标是让我们对数字化将如何影响能源部门脱碳途径的理解发生阶段性变化。物联网促进智能家电、存储、智能合约或电动汽车集成的潜力将支持不稳定、不确定、复杂和模糊（VUCA）场景，这些场景需要通过架构解决方案、新的价值流和有效实施的必要框架来解决。在这项范围界定研究中，我们将根据其创新方向、潜在影响和变化速度评估五个新兴领域（领域），以便优先考虑可实现的研究主题，并为未来研究其协同作用制定研究框架。这一过程将创建一个概念验证系统模型，用于分析能源转型，从而嵌入基于我们期望在未来运营能源系统中发现的技术的新分析方法。这一能源转型的概念验证将支持VUCA场景中能源系统转型的主要合作提案，展示网络、物理和社会系统如何无缝交织。我们认为，这项范围界定研究是成功过渡到数字数据驱动的能源未来的重要先导，从而改善人们的生活以及与能源环境的互动。该计划的目标包括寻找机会捕捉现实世界的数据，例如来自社交媒体、智能电表的数据，这些数据表明能源供需模式的变化和创新，并利用这些数据得出改进的过渡路径。

This study's overarching goal is to create a step change in our understanding of how digitalisation will impact on the pathway to decarbonise the energy sector. The potential of the Internet of Things promoting the integration of Smart appliances, Storage, Smart Contracts or Electrical Vehicles will underpin volatile, uncertain, complex and ambiguous (VUCA) scenarios that need to be addressed with architectural solutions, new value streams, and necessary frameworks for effective implementations. Within this scoping study we will evaluate five emergent fields (domains) in terms of their innovative directions, potential impact and pace of change in order to prioritize achievable research themes and develop a research framework for future study of their synergies. This process will create a proof of concept systems model for use in analysis of the energy transition, thereby embedding novel analytical approaches based on technologies that we expect to find in operational energy systems in the future. This proof of concept for energy transition will underpin a major collaborative proposal on energy system transition in VUCA scenarios demonstrating how cyber, physical and social systems are seamlessly interwoven. We consider this scoping study is an essential precursor for successful transition to digital data-driven energy futures enhancing people's lives and interactions with their energy environment. The ambition includes identifying opportunities to capture real-world data, such as that from social media, smart meters, which suggest changing and novel patterns of energy supply and demand, and to use this to derive improved transition pathways.