Multicriteria Genetic Tuning for the Optimization and Control of HVAC Systems
BibTeX
@MISC{Alcala_multicriteriagenetic,
author = {Rafael Alcala and Jose Manuel Benitez and Jorge Casillas and Juan Luis Castro and Oscar Cordon and Antonio Gonzalez and Francisco Herrera and Raul Perez},
title = {Multicriteria Genetic Tuning for the Optimization and Control of HVAC Systems},
year = {}
}
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Abstract
This work presents the use of genetic algorithms for the optimization and control of Heating, Ventilating and Air Conditioning (HVAC) systems developing smartly tuned fuzzy logic controllers for energy efficiency and overall performance of these systems. An optimum operation of the HVAC systems is a necessary condition for minimizing energy consumptions and optimizing indoor comfort in buildings. This problem has some specific restrictions that make itvery particular and complex because of the large time requirements existing due to the need of considering multiple criteria (which enlarges the solution search space) and to the long computation time models require to assess the accuracy of each individual. To solve these problems, three efficient genetic tuning strategies, considering different multicriteria approaches, have been presented and tested in two realtest sites (buildings) obtaining satisfactory results.
