Fuzzy Cognitive Maps (FCMs) are a very simple, useful and powerful tool for modeling and analyzing dynamic complex systems. They are suitable for processes where fuzziness and uncertainty are dominant characteristics. As the need for a fuzzy approach in modeling complex systems increases, so does the need to re-approach Fuzzy Cognitive Maps in order to make them more efficient. This paper marches towards this new approach as it attempts to address some of the well known drawbacks of Fuzzy Cognitive Maps. An energy model for the simulation of a building's automation system and the calculation of its consumption is being used as a case study. The results are presented and briefly discussed.