The traditional wind farm power dispatch approach prioritizes either power output or investment costs. Wind farm optimization is a critical task because it involves the installation of numerous turbines and equipment. Wake loss is a significant factor in substation power, reducing the wind farm's energy output downstream of the upstream wind turbines (WTs). While separating, the turbines can reduce wake losses and result in higher connection costs, which may not be a wise investment. The effectiveness of the wind farm is affected by many factors, including the electrical system equipment chosen, the number and placement of substations, and the layout of the cable connections. Considering energy yields, wake losses, and electrical system power losses, this article seeks to lower wind farms' Levelized Production Cost (LPC). A case study was conducted with a wind farm in the Western Cape of South Africa using an optimal power dispatch (OPD) technique. When comparing the OPD approach to the standard Maximum Power Point Tracking (MPPT) method, the LPC of the wind farm can be lowered. It has been demonstrated that particle swarm optimization (PSO) can enhance electrical system design, reduce costs and losses, boost energy production, and fulfill the operational needs of a power grid. The case study results show that this optimization control strategy for wind farms is feasible and effective.