This paper addresses the problem of managing battery energy in urban and rural alternating current networks, aiming at improving their financial, technical, and environmental indicators. To this end, a mathematical model was formulated that proposes as objective functions the optimization of energy operational costs of the grid, the minimization of power losses associated with energy transport, and the reduction in CO2 emissions related to the production of energy. This model also considers the set of constraints involved in the operation of an alternating current network in an environment with distributed energy resources (Photovoltaic generators + Batteries storage systems). A master-slave strategy that combines a parallel version of the Vortex Search Algorithm (VSA) and an Hourly Power Flow method based on Successive Approximations (HPFSA) was proposed as the solution methodology. To create the test scenarios, urban and rural electrical networks documented in the specialized literature were adapted using generation and demand data of an average day of operation in Medellin-Antioquia (Urban) and Capurgana-Choco (Rural). These data represent the energy behavior of an urban and a rural network within the Colombian territory. In relation to the distributed energy devices, the integration of three Photovoltaic Distributed Generators (PV DGs) and three lithium-ion batteries of different types into the electrical networks was considered. In addition, the energy production costs and CO2 emissions of the local network and the diesel fuel in Colombia were determined, as well as the maintenance costs associated with the batteries and the PV DGs. With the purpose of validating the effectiveness of the proposed method in terms of solution, repeatability, and processing times, two comparison methods reported in the specialized literature were employed to solve the problem addressed in this paper. In the urban and rural networks under study, the proposed solution methodology achieved the best results in terms of solution quality, repeatability, and processing time.