This paper proposes a multi-objective optimization method for solving the Security-Constrained Optimal Power Flow (SCOPF) problem with the consideration of solar farm integrated and distributed load variations in the grid. In this scheme, the power generated by solar farm is affected by the weather uncertainty. The dispatch objectives are formulated to minimize fuel cost and emission simultaneously. The computational complexity of such proposed multi-objective optimization is significantly higher than conventional dispatch scheme. Therefore, this research adopts a Bacterial Swarm Algorithm (BSA), which is more effective than most Evolutionary Algorithms (EAs). This paper reports the simulation results obtained using the IEEE 30-bus system, including a comparison study between the results achieved using the proposed method and those obtained from conventional dispatch methods. The trade-off relationships between fuel cost and emission are analysed based on the Pareto set of feasible solutions resulted from BSA.