<p>This study aims to address critical energy challenges in ports and maritime terminals by employing smart grid capabilities, such as distributed generation (DG) and demand-side management (DSM), to enhance energy efficiency and environmental sustainability. With the rise of renewable energy technologies, integrating photovoltaic (PV) systems with storage solutions has become essential for reducing reliance on traditional energy sources and managing load demands. The research proposes a mixed-integer linear programming (MILP) model to optimize energy consumption and mitigate the risk of overvoltage issues caused by reverse power flow from ports. The MILP model's core optimization objective is to minimize total daily electricity costs through coordinated scheduling of PV generation, battery storage operation, and flexible load shifting, subject to key constraints including: (1) voltage magnitude limits (0.95–1.05 p.u.) across all network buses to ensure power quality, (2) battery state of charge bounds (10–90% capacity) and charge/discharge rate limits to preserve battery lifespan, (3) shiftable load operational windows and cumulative energy requirements to maintain service quality, (4) power balance equations ensuring supply–demand equilibrium at each time interval, and (5) network power flow constraints governing the radial distribution system. The model incorporates dynamic load shifting, battery storage control, and PV power injection strategies to manage energy costs and ensure grid stability. The optimization model was implemented in GAMS and MATLAB and tested on the IEEE 33-bus distribution network to evaluate its effectiveness under stochastic scenarios generated via Monte Carlo simulation and reduced using probabilistic distance methods. Simulation results demonstrate that the proposed model effectively manages flexible port loads and energy storage systems while optimizing PV power injection into the grid. During low grid electricity price periods or high solar power generation, port loads are shifted accordingly to minimize energy costs while maintaining service quality. Additionally, surplus PV energy is stored or injected into the grid to stabilize voltage profiles. The findings highlight significant cost savings for port consumers (59% reduction under dynamic pricing schemes) and improved voltage profiles, with the model maintaining all bus voltages within IEEE 1547 standards across 25 stochastic scenarios while achieving 15–20% peak demand reduction and 25–30% renewable energy utilization improvement. The proposed approach successfully leverages smart grid technologies to transform ports from mere energy consumers to active participants in grid support, reducing energy costs and enhancing voltage stability. Future research should explore optimizing EV charging station management in ports, strategically locating energy storage, and developing competitive strategies for ports with integrated renewable energy, responsive loads, and DG units to further advance voltage control, congestion management, and environmental benefits in smart grid environments.</p>