**6. Conclusions**

A novel model to include customer's satisfaction in an optimization problem was introduced. A quantifiable user satisfaction was developed. The satisfaction concept through the novel concepts of power satisfaction (PS) and energy satisfaction (ES) included the detrimental impact that excess consumption could have in the quality of life. The algorithm provided the hours of the day for which the energy should be allocated to achieve maximum satisfaction at an energy constraint imposed by the energy consumption in actual case scenarios. Actual case scenarios were represented by using the REDD database. The Shapley Value (SV) concept from the game theory framework was implemented to obtain a recommendation on how energy should be allocated. The results showed how the algorithm maximized user´s ES at a minimum energy consumption. The proposed approach reduced energy consumption 75%, while increasing ES 40%.

SV-based optimization successfully achieved to maximize satisfaction at a minimum energy consumption although it also has high computational complexity. Further work can be done to decrease computational complexity and thus the required reduction processing times. This could be achieved by using more powerful computers or through the derivation recursive and/or parallel implementation of the proposed algorithm. The proposed methodology is validated by simulating a rural single house with limited resources connected to the grid. It should be pointed out that the satisfaction model can be readily applied in a real case scenario of rural communities.

**Author Contributions:** Conceptualization, S.O., and M.C.-S.; data curation, S.O.; formal analysis, S.O.; funding acquisition, M.C.-S.; investigation, S.O.; methodology, S.O. and M.N.; software, S.O.; validation, S.O.; visualization, S.O.; writing—original draft, S.O.; writing–review and editing, S.O., M.N. and M.C.-S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This document is the result of the research project partially funded by the National Science Foundation through the project titled "Cultivating Responsible Wellbeing in STEM: Social Engagement through Personal Ethics", award #1449489, at the University of Puerto Rico in Mayagüez.

**Data Availability Statement:** Public REDD dataset can be found at http://redd.csail.mit.edu/.

**Conflicts of Interest:** The authors declare no conflict of interest.
