Energy Management System Based on a Gamified Application for Households

Manuel Avila, Juana Isabel Méndez, Pedro Ponce, Therese Peffer, Alan Meier and Arturo Molina
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Manuel Avila: School of Engineering and Sciences, Tecnologico de Monterrey, Mexico City 14380, Mexico
Juana Isabel Méndez: School of Engineering and Sciences, Tecnologico de Monterrey, Mexico City 14380, Mexico
Pedro Ponce: School of Engineering and Sciences, Tecnologico de Monterrey, Mexico City 14380, Mexico
Therese Peffer: Institute for Energy and Environment, University of California, Berkeley, CA 94720, USA
Alan Meier: Energy and Efficiency Institute, University of California, Davis, CA 95616, USA
Arturo Molina: School of Engineering and Sciences, Tecnologico de Monterrey, Mexico City 14380, Mexico

Energies, 2021, vol. 14, issue 12, 1-27

Abstract: Nowadays, the growth in the consumption of energy and the need to face pollution resulting from its generation are causing concern for consumers and providers. Energy consumption in residential buildings and houses is about 22% of total energy production. Cutting-edge energy managers aim to optimize electrical devices in homes, taking into account users’ patterns, goals, and needs, by creating energy consumption awareness and helping current change habits. In this way, energy manager systems (EMSs) monitor and manage electrical appliances, automate and schedule actions, and make suggestions regarding electrical consumption. Furthermore, gamification strategies may change energy consumption patterns through energy managers, which are seen as an option to save energy and money. Therefore, this paper proposes a personalized gamification strategy for an EMS through an adaptive neuro-fuzzy inference system (ANFIS) decision-making engine to classify the level of electrical consumption and persuade the end-user to reduce and modify consumption patterns, saving energy and money with gamified motivations. These strategies have proven to be effective in changing consumer behavior with intrinsic and extrinsic motivations. The interfaces consider three cases for summer and winter periods to calculate the saving-energy potentials: (1) for a type of user that is interested in home-improvement efforts while helping to save energy; (2) for a type of user that is advocating to save energy; (3) for a type of user that is not interested in saving energy. Hence, each interface considers the end-user’s current consumption and the possibility to modify their consumption habits using their current electrical devices. Finally, an interface displaying the electrical consumption for each case exemplifies its linkage with EMSs.

Keywords: energy management system; gamification; smart home; HMI; ANFIS; HVAC; thermostat; tailored products (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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