Delivering community energy flexibility through space heating - analysis and optimisation of energy system design and control strategies

The energy landscape is profoundly shifting worldwide to mitigate climate change and reduce global CO2 emissions. The electrification of heating and transportation, as well as the deployment of renewable energy sources, is a crucial factor in the decarbonisation of the energy ecosystem. However, electrifying heating and transport exacerbate peak electricity demand while the rising penetration of renewable energy sources in the energy mix increases supply variability and network volatility. This presents a fundamental challenge for the operation and management of future energy systems, highlighting the need for diverse sources of energy flexibility, particularly considering the decline of traditional flexibility sources such as old gas and coal power plants.

This study aims to investigate the extent to which the incorporation of flexible heating in buildings into the design of community energy systems can result in the efficient management of energy demand. The study considers a community of dwellings representing conventional geometries, construction materials, and occupancy schedules of UK residential buildings. The proposed case study models entail the utilisation of a bottom-up modelling approach to simulate building energy systems at the household level. Each building in the community is equipped with an air to water heat pump and radiators to provide space heating to the building. To extend the flexibility capacity of the community, a rooftop solar PV and electrical battery storage is implemented in each dwelling and interconnected with the grid.

This research investigates the implications of implementing a rule-based control (RBC) strategy, which involves regulating the operation of buildings and HVAC systems based on predetermined rules, to optimise energy systems and dispatch operations to reduce energy demand while maintaining thermal comfort. The community is exposed to time-varying electricity prices. A comparison of the baseline with the flexible control scenarios is evaluated. Due to better energy arbitrage and the optimal selection and sizing of energy systems, the optimal flexible control yielded a 7% of annual demand reduction and 47% load shifting during peak demand periods. The integration of Solar PV and battery storage resulted in a 44% reduction in annual demand, 40% usage of self-generated energy and 80% load shifting during peak demand periods. Utilising RBC that optimised demand reduction during peak demand periods curtailed the load profile of the community from 2080 kW to 130 kW between the hours of 8:00 – 9:00, on the coldest day.

The findings of the study highlight the impact of weather patterns, thermal efficiency of dwellings, energy systems, and control mechanisms on the delivery of energy flexibility. The approach used in the study provides valuable insights into the technical aspects of implementing energy flexibility in consumer and prosumer communities. These insights contribute to a better understanding of the factors that influence the successful activation of energy flexibility in such communities.