Abstract: To maximize the comprehensive benefits of the reservoir and ensure its optimal operation, this study integrates the reservoir power generation module into a water-sediment dynamics model that accurately describes water and sediment transport and calculates the sedimentation and erosion in the reservoir area. A genetic algorithm based on Gaussian dynamic distribution variation operators is used to calculate the optimal scheduling of the reservoir, resulting in the development of an optimization scheduling model for sediment reduction and power generation. This model is applied to the Sanmenxia Reservoir for water-sediment-electricity simulation validation, with the downstream discharge flow rate as the decision variable in the optimization scheduling study. The results show that the water-sediment-electricity model can accurately simulate the water level and flow process at various measuring stations in the reservoir, with errors in sediment accumulation and power generation calculations both less than 5%. The water-sediment dynamics model effectively integrates with the genetic algorithm for optimization scheduling. By adjusting the reservoir water level during the flood season, the power generation increased by 28%, while the sediment erosion in the reservoir area was reduced by 8.8%. This research provides a reference for multi-objective optimization scheduling of reservoirs in heavily sediment-laden rivers.