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Adjustment of Multiple Variables for Optimal Control of Building Energy Performance via a Genetic Algorithm

Author(s):


Medium: journal article
Language(s): English
Published in: Buildings, , n. 11, v. 10
Page(s): 195
DOI: 10.3390/buildings10110195
Abstract:

Optimizing the operating conditions and control set points of the heating, ventilation, and air-conditioning (HVAC) system in a building is one of the most effective ways to save energy and improve the building’s energy performance. Here, we optimized different control variables using a genetic algorithm. We constructed and evaluated three optimal control scenarios (cases) to compare the energy savings of each by varying the setting and number and type of the optimized control variables. Case 1 used only air-side control variables and achieved an energy savings rate of about 5.72%; case 2 used only water-side control variables and achieved an energy savings rate of 16.98%; and case 3, which combined all the control variables, achieved 25.14% energy savings. The energy savings percentages differed depending on the setting and type of the control variables. The results show that, when multiple control set points are optimized simultaneously in an HVAC system, the energy savings efficiency becomes more effective. It was also confirmed that the control characteristics and energy saving rate change depending on the location and number of control variables when optimizing using the same algorithm.

Copyright: © 2020 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10474359
  • Published on:
    31/10/2020
  • Last updated on:
    02/06/2021