A method is proposed to optimize the placement of Photovoltaic Power Plants (PVPP) within High Voltage Electric Distribution Systems (EDS) to minimize electrical losses and achieve Minimum Global Cost (MGC). Integrating Digital Image Processing (DIP) with metaheuristic algorithms like Genetic Algorithm (GA) and Tabu Search (TS), real EDS data, including existing PVPP, was utilized. Results across three scenarios (10 MWp, 20 MWp, and 50 MWp) consistently identified the best bus as the optimal location, achieving reductions in annual energy losses of 8.55%, 14.89%, and 16.81%, with corresponding payback periods (PP) of 12.0, 7.78, and 5.71 years respectively. Statistical analysis indicated that both GA and TS effectively addressed the problem, with TS showing lower variability in finding optimal solutions compared to GA. This approach demonstrates significant technical and economic benefits in optimizing PVPP location and sizing within EDS.