Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm

Energy ◽  
2009 ◽  
Vol 34 (1) ◽  
pp. 58-66 ◽  
Author(s):  
M MOSSOLLY ◽  
K GHALI ◽  
N GHADDAR
2013 ◽  
Vol 671-674 ◽  
pp. 2515-2519
Author(s):  
Xue Mei Wang ◽  
Zhen Hai Wang ◽  
Xing Long Wu

This project aims to study the optimal control model of the ice-storage system which is theoretically close to the optimal control and also applicable to actual engineering. Using Energy Plus, the energy consumption simulation software, and the simple solution method of optimal control, researchers can analyze and compare the annual operation costs of the ice-storage air-conditioning system of a project in Beijing under different control strategies. Researchers obtained the power rates of the air-conditioning system in the office building under the conditions of chiller-priority and optimal contro1 throughout the cooling season. Through analysis and comparison, they find that after the implementation of optimal control, the annually saved power bills mainly result from non-design conditions, especially in the transitional seasons.


2019 ◽  
Vol 11 (18) ◽  
pp. 5122 ◽  
Author(s):  
Nam-Chul Seong ◽  
Jee-Heon Kim ◽  
Wonchang Choi

This study is aimed at developing a real-time optimal control strategy for variable air volume (VAV) air-conditioning in a heating, ventilation, and air-conditioning (HVAC) system using genetic algorithms and a simulated large-scale office building. The two selected control variables are the settings for the supply air temperature and the duct static pressure to provide optimal control for the VAV air-conditioning system. Genetic algorithms were employed to calculate the optimal control settings for each control variable. The proposed optimal control conditions were evaluated according to the total energy consumption of the HVAC system based on its component parts (fan, chiller, and cold-water pump). The results confirm that the supply air temperature and duct static pressure change according to the cooling load of the simulated building. Using the proposed optimal control variables, the total energy consumption of the building was reduced up to 5.72% compared to under ‘normal’ settings and conditions.


2013 ◽  
Vol 655-657 ◽  
pp. 1492-1495
Author(s):  
Ting Wu ◽  
Gang Wu ◽  
Zhe Jing Bao ◽  
Wen Jun Yan

Ice storage air-conditioning system can bring benefits to power supplier and consumers for its advantage of shifting power consumption at peak hours during day to the off-peak hours at night. In this paper, we adopted an improved particle swarm optimization algorithm to develop an optimal control strategy for ice storage air-conditioning system with the aim of minimizing operation cost subject to various operational constrains. Comparing with the usual chiller-priority and ice-storage-priority control strategy, the proposed control scheme can not only meet the building cooling load but also achieve the minimum operation cost.


Author(s):  
Hongpu Liang

Abstract For areas with hot summer and cold winter, air conditioning is an essential tool to improve the living environment, but the traditional air conditioning needs to consume a lot of energy in cooling and heating, the fan operation noise is large and the sense of blowing will be uncomfortable. This paper briefly introduced the basic structure of a ground-source heat pump-floor radiant air conditioning system and the control strategy which was used for regulating the operation of the air conditioning system. Then, in order to ensure the appropriate comfort and reduce energy consumption, the control strategy was optimized. An experimental room in Xining, Qinghai province, was taken as an example for analysis. The results showed that the thermal comfort under the control strategy proposed in this study was more stable at the moderate degree and the temperature was slightly higher under the traditional control strategy, although the indoor temperature fluctuation under the optimal control strategy was large and the temperature was slightly lower than that under the traditional control strategy; under the control strategy proposed in this study, the air conditioning system had shorter operation time and less power consumption.


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