REVISTA DYNA ENERGÍA

Key words:

Optimización, Algoritmos de Enjambres de Partículas, Eficiencia Energética, Ciudades Inteligentes, Respuesta de la Demanda Eléctrica, Optimization, Particle Swarm Algorithms, Energy Efficiency, Smart Cities, Electric Demand Response

Article type:

ARTICULO DE INVESTIGACION / RESEARCH ARTICLE

Section:

RESEARCH ARTICLES

ABSTRACT:
This paper proposes a method that allows residential neighborhoods to take advantage of electricity low prices during off-peaks hours and, at the same time, avoid generating joint demand peaks.
The method is based on moving loads in the home (controllable devices such as appliances) to valley hours with low rates while simultaneously trying not coinciding in time in order to not generate joint peaks. To this end, an optimization algorithm generates electricity price profiles slightly different for each home. The profile is received in the home by an EMS (Energy Management System) that switches on the devices in the most economic moment, always trying to respect the preferences and habits of the users. It has been found that joint power peaks can be decreased and, at the same time, electricity cost savings can be achieved.
The optimization algorithm is based on particle swarm optimization method.

Key Words: Optimization, Particle Swarm Algorithms, Energy Efficiency, Smart Cities, Electric Demand Response