A fundamental unified framework to quantify and characterise energy flexibility of residential buildings with multiple electrical and thermal energy systems

摘要

To date, the energy flexibility assessment of multicomponent electrical and thermal systems in residential buildings is hindered by the lack of adequate indicators due to the different interpretations, properties, and requirements that characterise an energy flexible building. This paper addresses this knowledge gap by presenting a fundamental energy flexibility quantification framework applicable to various energy systems commonly found in residential buildings (i.e., heat pumps, renewables, thermal and electrical storage systems). Using this framework, the interactions between these systems are analysed, as well as assessing the net energy cost of providing flexibility arising from demand response actions where onsite electricity production is present. A calibrated white-box model of a residential building developed using EnergyPlus (including inter alia a ground source heat pump, a battery storage system, and an electric vehicle) is utilised. To acquire daily energy flexibility mappings, hourly independent, and consecutive demand response actions are imposed for each energy system, using the proposed indicators. The obtained flexibility maps give insights into both the energy volumes associated with demand response actions and qualitative characteristics of the modulated electricity consumption curves. The flexibility potential of each studied energy system is determined by weather and occupant thermal comfort preferences as well as the use of appliances, lighting, etc. Finally, simulations show that zone and water tank thermostat modulations can be suitably combined to shift rebound occurrences away from peak demand periods. These insights can be used by electricity aggregators to evaluate a portfolio of buildings or optimally harness the flexibility of each energy system to shift peak demand consumption to off-peak periods or periods of excess onsite electricity generation.