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ENERGY-SAVING OPTIMIZATION CONTROL METHOD OF COMMERCIAL BUILDING DOUBLE COLD SOURCE AIR-CONDITIONING UNITS

ABSTRACT
In order to improve the energy-saving level of commercial buildings’ air-conditioning units with double cold sources and reduce the energy cost, an energy-saving optimal control method of commercial buildings’ air-conditioning units with double cold sources based on self-organizing neural network is proposed. Constrained parameter model of energy-saving control of commercial buildings’ double-cold-source air-conditioning units is constructed. Taking the balanced real-time dynamic adjustment characteristic quantity of inverter of commercial buildings’ double-cold-source air-conditioning units as the control object, combined with the fuzzy constraint method of variable frequency speed adjustment parameters and stroke adjustment power of commercial buildings’ double-cold-source air-conditioning units, the steady-state adjustment of energy-saving output of commercial buildings’ double-cold-source air-conditioning units is realized, and the self-organizing neural network control model of periodic potential energy load of building HVAC system is established. Combined with the small disturbance suppression method of motor rated power, the optimal control design of energy-saving of commercial buildings. The simulation results show that the output stability of the energy-saving control of commercial building air-conditioning units with double cold sources is good, the steady-state working ability is strong, and the energy-saving effect of commercial building air-conditioning units with double cold sources is good.
KEYWORDS
PAPER SUBMITTED: 2022-01-10
PAPER REVISED: 2022-03-05
PAPER ACCEPTED: 2022-05-08
PUBLISHED ONLINE: 2022-06-04
DOI REFERENCE: https://doi.org/10.2298/TSCI220110081W
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2022, VOLUME 26, ISSUE Issue 4, PAGES [3545 - 3558]
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© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence