During the last century, population growth, together with economic development, has considerably increased the energy demand and, although renewable energies are becoming an alternative, still total energy supply is mainly non-renewable, causing well-known negative effects such as pollution and global warming. On the other hand, technological advances have allowed the development of increasingly efficient distributed generation systems and the emergence of microgrids, whose studies have been focused on architecture, elements, and objectives of the associated energy management strategies. In this regard, energy management strategies based on a Fuzzy Logic controller have been developed for electro-thermal microgrids where parameter optimization has been carried out through heuristic procedures of trial and error with acceptable results but involving a high computational cost. To solve the aforementioned drawbacks, in the present work the use of Cuckoo Search optimization nature-inspired algorithm that allows the adjustment of Fuzzy Logic controller parameters and ensures a higher quality of energy management is proposed. Obtained results show encouraging outcomes for the use of these meta-heuristic optimization algorithms.