Residential Energy Management System Based on Coevolutionary Particle Swarm Optimization

Driele P. da S. Ribeiro and Luiz C. P. da Silva


Electrical Systems, Energy and bioenergy, Metaheuristics, Home Energy Management System, GridLAB-D, Energy Conservation


This paper presents a methodology for energy management in residential consumers seeking for reduced costs with electricity. The technique gives a day ahead schedule that shows the best period of the day to switch on and off the pool pump, the dishwasher, the washing machine and the electric shower; home battery percentage of charge or discharge for each hour; and the hourly temperature adjustments of a Heating, Ventilation, and Air conditioning System (HVAC). In order to calculate the HVAC power consumption, the simulation software GridLAB-D was used. Also in GridLAB-D, real data for temperature and radiation were employed to simulate the power generation of Photovoltaic (PV) panels. The simulation was made with data from a northern city (Belém – PA) and a southern city (Santa Maria - RS) of Brazil, in order to compare the results for different weather conditions. For the remaining equipments, it was considered the average consumption according to the results provided by Procel-Eletrobras on consumer habits and ownership of appliances. To calculate the energy cost, current tariffs from each local company were used. To find the best solution, an optimization method based on Particle Swarm Optimization (PSO), and a variation with a coevolutionary approach were chosen.

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