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Wind farms (WFs) appear to generate greater energy output with increasing integration of renewable energy in recent years by Wind Turbines (WTs). To achieve the goal, a number of WFs have a construction layout consisting of a series of turbines placed in the vicinity within a limited space of the terrain, which leads to augmented energy losses because of the “wake effects." Therefore, WTs on a wind farm to enhance the generated energy while meeting all constraints are quite restrictive and complicated. The Sparrow Search Algorithm (SSA) that has just been created in this article was chosen as the most appropriate method of searching where wind turbines are located within an area of WFs to achieve maximum turbine capacity at minimum cost, which will translate to increased power efficiency. Two scenarios were taken into consideration: one factor took into account constant wind speed and changing wind direction, while the other took into account changing wind speed and changing wind direction. The constructed framework was contrasted with the outcomes of the previous studies which address the same issue. Therefore, the proposed algorithm gave a good algorithm to tackle the wind turbine placement problem to attain optimal placement.