Energy management systems can provide a variety of features and services to prosumers. One of its most important functions is to determine cost-effective energy mixing rates by evaluating the unit price and power of energy resources. This study mainly proposes a hybrid optimization based on two heuristic algorithms: Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) algorithms. A hybrid ABC-PSO algorithm has been applied to solve the energy efficient multi-source energy mixing problem in Matlab. The proposed algorithm has been tested in the simulation of an energy management system including a grid, solar panel, wind turbine, and storage unit. The results show that the proposed algorithm responds appropriately to meet the hourly changing demand of the consumer in cases of energy production fluctuations in renewable energy sources and dynamic electricity price tariff implementation of the grid. This method can provide cost efficiency by maintaining the energy balance of consumers in smart grids. The algorithm has a simple structure, thus the method provides a solution for low-cost energy management applications in the microgrid.