This research aims to explore the behavioural diversity and bounded rationality within an Energy Hub (EH) under congestion management with a modelling tool such as Agent-Based Modelling (ABM). The model incorporated rotational load shedding, adaptive capacity allocation, PV panels, and a dashboard. The model also incorporated behavioural drivers, such as the symbiosis of participants with different Social Value Orientations (SVO) and other factors that influences load shifting. The ABM was compared with real-world data of participants in an EH. The results show that altruistic and pro-social populations perform the best in short-term, while the competitive populations adapt over time in long-term. Gamification could be a strategy to use the social factors to engage diverse participants in interactive activities and support collaboration. Time-of-Use (ToU) pricing could be a strategy to add next to the dashboard to engage diverse competitive and individualistic participants to load shift. Proportional load shedding could be another strategy to provide for a more equitable way to load shedding. This study provides a system-level perspective, showing how heterogenous and homogenous IC compositions influence demand response outcomes. This model can be used in future case studies to analyse collaboration patterns, test interventions, and the recommended strategies.