In the present research two new methods to select optimal suppliers considering component replacement policies for a micro-grid were developed, the main objectives considered in the replacement problem are to minimize the overall system costs (operation cost, maintenance cost), as well as maximize the overall system efficiency. Once the replacement schedules are generated, we propose two methods, a) Euclidean Distance and b) Ideal Vector System) to select suppliers to replace components in the system. The methods are applied to a previously designed micro-grid, the Euclidean Distance method looks for solutions (vectors) defined by the closest distance that most closely resembles the desired (ideal) vector (solution), which is the one with a smaller distance to the ideal vector, the closest solution, as defined by the Euclidean distance, will be the one the one that offers in this case a more efficient condition to the characteristics of efficiency and system cost,  among others. The second method proposed in the present work, the ideal vector system, considers the gains that exist between the characteristics of the participating vectors (solutions), for example, cost is a characteristic for which the negative gain becomes a positive gain for this algorithm, and characteristics such as component life considering the longer components’ life the better for the system. The final solution is found in the vector that defines the highest gain; all characteristics are converted into a vector in values per unit referenced to a desired vector established by the decision maker. The proposed methods are applied to a microgrid previously generated by using a microgrid design allocation algorithm and after running a component replacement analysis model. Finally, the two proposed methods are applied to a microgrid and both methods converge to select the same suppliers to replace components in the micro-grid.