Energy system models (ESMs) inform the transition from fossil fuels to renewable energy. Optimal system design is influenced by the shape and magnitude of electricity demand. Demands will change as decarbonisation efforts across sectors aim at electrification. However, many ESMs oversimplify the complexity of demand changes driven by individual adoption decisions. Agent-based models (ABMs) allow for incorporating behavioural theories capturing this complexity, but rely on assumptions about factors like energy prices and emissions affecting adoption behaviour. This work introduces a novel framework, CanAdopt, that integrates an ABM with an ESM, alleviating assumption requirements in both models. The capabilities of the novel framework are demonstrated for scenario analysis of policy impacts in the energy and residential heating sectors. The ABM models heating technology adoption and residential electricity demands for the ESM, which optimises capacity expansion and yields electricity prices and embedded emissions for the ABM. Both models cover 2020–2050 and are executed sequentially eight times. Applied to Ontario, Canada, the most progressive scenario achieves net-zero by 2035 and 2040 in the residential sector and power sector, respectively. The total transition costs are 327 billion CAD in the residential sector and 395 billion CAD in the power sector. Cumulative heating related emissions increase by 43% through a five-year delay in achieving net-zero, underscoring the urgency of the transition. The governmental carbon abatement costs in the residential sector range from 72 to 110 CAD/(t CO₂), well below the federal carbon tax of 170 CAD/(t CO₂). The coupling of both models showed, that increased residential heat pump adoption may reduce total transition cost by 8 to 10 billion CAD in the power system, but the increases in demand may be challenging to meet if additionally electric furnaces are widely adopted.