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A generic framework is developed to study the application of energy hubs and its related network model to demonstrate the optimal design and operation of distributed energy systems (DESs) in urban areas. A novel multi-objective approach based on augmented epsilon constraint technique is employed to carry out this work. As an illustrative example, the proposed model is applied to an urban area in Ontario, Canada. Different scenarios are defined to investigate the effect of energy storage systems and energy exchange within a network on the optimal configuration and operation of the system. Moreover, multi-objective optimization is carried out based on two conflicting objectives, namely, total annual cost and greenhouse gas emission. The findings show that the simultaneous consideration of DESs, storage technologies, and a network of energy exchange between hubs (scenario 4) results in the installation of more DESs and at least 8% reduction of annual cost when compared to other scenarios. Furthermore, lowering the electricity grid emission factor results in higher adoption of renewable energy generation based DESs rather than natural gas based DESs. The sensitivity analysis shows that doubling the electricity tariff rate results in 75% increase in cost, while the pricing of natural gas has no significant effect on overall cost. This demonstrates that the cost is more sensitive to the electricity tariff rate rather than natural gas price for this specific case study.