This study develops an integrated optimization model for the urban electricity supply chain of Tehran Province by integrating economic planning with environmental life cycle assessment (LCA). The model determines decisions regarding fuel supply, power generation capacity expansion, electricity generation, and electricity imports from the grid over the 2026–2050 planning horizon. The proposed model is formulated as a mixed-integer linear programming (MILP) model. Environmental impacts of electricity supply chain activities are evaluated across three damage categories—resource depletion, ecosystem damage, and human health—and monetized and internalized within the objective function. Model performance is evaluated by comparing two approaches: minimizing economic costs alone and jointly minimizing economic and environmental costs. Fuel price is considered the most important sensitivity parameter. The results show that under the economic objective, total economic cost over the planning horizon is approximately USD 91 billion, whereas under the economic–environmental objective, a 4.1% increase in economic cost reduces total environmental cost by approximately 20.8%. Furthermore, internalizing environmental costs can alter the technology mix and capacity expansion pathway and reduce dependence on electricity imported from the grid. Fuel-price sensitivity analysis shows that lower fuel prices increase the economic attractiveness of thermal generation and fossil-fuel dependence under the economic objective, whereas the economic–environmental objective results in greater deployment of renewable technologies. From a policy perspective, gradual fuel price reform combined with environmental cost internalization can help prevent part of the hidden costs of electricity supply from being shifted to sectors such as healthcare and the environment.