Cyber-Physical Energy Systems: Enabling Tailored Decarbonization and NetZero Pathways for Communities

Given the urgency of the climate crisis and the vulnerabilities of communities to energy poverty, it is critical that we radically decarbonise whilst cognisant of the needs of people and place. Regional net-zero planning as to integrate whole system optimisations for communities e.g. coupling of electricity, heat, and transport vectors, is vital to timely and affordable decarbonisation. In this work, we propose a Cyber-Physical Energy System (CPES) architecture and smart local energy system design framework as to integrate real-time monitoring, machine learning and AI based services to optimise a district's energy consumption and streamline data management for decarbonization initiatives. Specifically, the framework proposed in this work is agnostic of the technology used and allows interoperability and coordination of multi-physics sensing and actuator assets. This framework was implemented on a real and large-scale use case from The Crichton Trust estate in Dumfries, UK. We explore the potential economic savings through low-cost solutions and operational adjustments, alongside highlighting the importance of data collection in preserving the heritage values of these buildings. By implementing the CPES architecture and digital energy services, we assess the benefits of streamlined processes, real-time visualization, accurate forecasting, and efficiency tracking, ultimately leading to substantial cost savings for the estate. Our findings indicate a significant reduction in natural gas usage (15-28%), achieved by optimizing heat demand within a heritage building. Extrapolating these savings across similar assets across the entire estate could yield an annual cost reduction of £65, 000-£132, 000, based on current energy unit prices.