Air Conditioning Units Optimize Control Strategy Based on Multi-Objective Optimization Evolutionary Algorithms

In order to reduce the energy consumption of air conditioning systems, the best running model is adjusting the humiture according to actual needs of environment and groups.This paper take out a control strategy based on the Multi-objective Optimization Evolutionary Algorithms.With cntrol simulation, it achieve the energy saving effect in air conditioning units groups, proposed multi-objective optimization control strategy.

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Energy Conservation Analysis for Air Conditioning System in Rail Transit Stations

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.494-495.1674 ◽

2014 ◽

Vol 494-495 ◽

pp. 1674-1677

Author(s):

Bing Xu ◽

Fang Hong Yuan ◽

Bao Guo Zheng ◽

Zhong Jin Shi ◽

Yi Huan Hu

Keyword(s):

Energy Consumption ◽

Energy Conservation ◽

Energy Saving ◽

Control Strategy ◽

Air Conditioning ◽

Rail Transit ◽

Air Conditioning System ◽

Conservation Analysis ◽

Air Conditioning Systems ◽

Reducing Energy

This article discusses energy conservation for air conditioning systems in rail transit stations. At first, the paper analyzes the energy consumption condition in the air conditioning systems in rail transit stations. Then, it discusses application of appropriate control strategy for reducing energy consumption. In the end, the paper calculates effiency and amount of the energy saving based on the control strategy.

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Research on Comprehensive Energy Saving Control Strategy of Air Conditioning

Design Engineering ◽

10.17762/de.vi.973 ◽

2020 ◽

pp. 130-140

Author(s):

Guozeng Wu , Tao Li , Yijin Gang

Keyword(s):

Energy Consumption ◽

Energy Saving ◽

Control Strategy ◽

Air Conditioning ◽

Control Algorithm ◽

Environmental Indicators ◽

Air Conditioning System ◽

Saving Effect ◽

Energy Saving Control ◽

Conditioning Control

On the basis of ensuring the requirements of process air parameters, the air conditioning control should reduce the energy consumption of the air conditioning system to the maximum extent. In this paper, by improving the adjusting speed and stability of the air conditioning system, and according to the process of environmental indicators allow deviation of belt, on the premise of not beyond the maximum technical index requirements by control algorithm to achieve better energy saving effect.

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Strategy of Intelligent Energy-Saving Optimization Control and Energy Consumption Analysis on Regulator Control System of Closed Greenhouse

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.666.184 ◽

2014 ◽

Vol 666 ◽

pp. 184-187

Author(s):

Min Gyu Zhang ◽

Guang Hua Wu ◽

Feng Liu

Keyword(s):

Energy Consumption ◽

Energy Saving ◽

Control Strategy ◽

Energy Optimization ◽

Saving Rate ◽

Integration Strategy ◽

Energy Consumption Analysis ◽

Optimization Control ◽

Optimizing Control ◽

Saving Effect

Adopting the integrated TOPSIS intelligent energy optimization control strategy, and compared to conventional single control strategy on energy consumption of greenhouse equipment under closed condition, this paper arrives at the best energy saving optimization control strategy with comprehensive benefits. The result shows that, integrated intelligent optimizing control was obviously more energy saving compared to those did not take optimization control. Specific results as follows: TOPSIS integration strategy with energy saving of 725.39kwh, energy-saving rate of 44.19%.This shows that the proposed integrated intelligent energy optimization control strategy and energy saving effect is remarkable.

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Systematic Method for the Energy-Saving Potential Calculation of Air-Conditioning Systems via Data Mining. Part I: Methodology

Energies ◽

10.3390/en14010081 ◽

2020 ◽

Vol 14 (1) ◽

pp. 81

Author(s):

Rongjiang Ma ◽

Shen Yang ◽

Xianlin Wang ◽

Xi-Cheng Wang ◽

Ming Shan ◽

...

Keyword(s):

Data Mining ◽

Energy Consumption ◽

Energy Saving ◽

Air Conditioning ◽

Storage System ◽

Operation Mode ◽

Systematic Method ◽

Potential Analysis ◽

Energy Saving Potential ◽

Air Conditioning Systems

Air-conditioning systems contribute the most to energy consumption among building equipment. Hence, energy saving for air-conditioning systems would be the essence of reducing building energy consumption. The conventional energy-saving diagnosis method through observation, test, and identification (OTI) has several drawbacks such as time consumption and narrow focus. To overcome these problems, this study proposed a systematic method for energy-saving diagnosis in air-conditioning systems based on data mining. The method mainly includes seven steps: (1) data collection, (2) data preprocessing, (3) recognition of variable-speed equipment, (4) recognition of system operation mode, (5) regression analysis of energy consumption data, (6) constraints analysis of system running, and (7) energy-saving potential analysis. A case study with a complicated air-conditioning system coupled with an ice storage system demonstrated the effectiveness of the proposed method. Compared with the traditional OTI method, the data-mining-based method can provide a more comprehensive analysis of energy-saving potential with less time cost, although it strongly relies on data quality in all steps and lacks flexibility for diagnosing specific equipment for energy-saving potential analysis. The results can deepen the understanding of the operating data characteristics of air-conditioning systems.

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A multi-objective operation strategy optimization for ice storage systems based on decentralized control structure

Building Services Engineering Research and Technology ◽

10.1177/0143624420966259 ◽

2020 ◽

Vol 42 (1) ◽

pp. 62-81

Author(s):

Yanhuan Ren ◽

Junqi Yu ◽

Anjun Zhao ◽

Wenqiang Jing ◽

Tong Ran ◽

...

Keyword(s):

Energy Saving ◽

Decentralized Control ◽

Optimization Algorithm ◽

Control Strategy ◽

Load Distribution ◽

Air Conditioning ◽

Control Structure ◽

Ice Storage ◽

Swarm Optimization ◽

Multi Objective

Improving the operational efficiency of chillers and science-based planning the cooling load distribution between the chillers and ice tank are core issues to achieve low-cost and energy-saving operations of ice storage air-conditioning systems. In view of the problems existing in centralized control architecture applied in heating, ventilation, and air conditioning, a distributed multi-objective particle swarm optimization improved by differential evolution algorithm based on a decentralized control structure was proposed. The energy consumption, operating cost, and energy loss were taken as the objectives to solve the chiller’s hourly partial load ratio and the cooling ratio of ice tank. A large-scale shopping mall in Xi’an was used as a case study. The results show that the proposed algorithm was efficient and provided significantly higher energy-savings than the traditional control strategy and particle swarm optimization algorithm, which has the advantages of good convergence, high stability, strong robustness, and high accuracy. Practical application: The end equipment of the electromechanical system is the basic component through the building operation. Based on this characteristic, taken electromechanical equipment as the computing unit, this paper proposes a distributed multi-objective optimization control strategy. In order to fully explore the economic and energy-saving effect of ice storage system, the optimization algorithm solves the chillers operation status and the load distribution. The improved optimization algorithm ensures the diversity of particles, gains fast optimization speed and higher accuracy, and also provides a better economic and energy-saving operation strategy for ice storage air-conditioning projects.

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Energy Consumption Analysis on Office Building Ventilation

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.516-517.1139 ◽

2012 ◽

Vol 516-517 ◽

pp. 1139-1143

Author(s):

Ke Chun Sun ◽

Wei Jun Zhang

Keyword(s):

Energy Consumption ◽

Energy Saving ◽

Air Conditioning ◽

Room Temperature ◽

Simulation Analysis ◽

Simulation Software ◽

Energy Simulation ◽

Office Building ◽

Saving Effect ◽

Night Ventilation

Chongqing weather conditions as the representative, energy simulation software DesT-c Chongqing office building energy simulation analysis, simulated natural building under different ventilation conditions at room temperature, the energy consumption of building cooling load and air-conditioning system changes, with an emphasis on energy-saving effect of the night ventilation; The study showed that in Chongqing reasonable use of ventilation reduce building natural room temperature to a certain extent; Sensitive indicators of building air conditioning energy consumption than the heating energy consumption of ventilation was significantly; Night ventilation when the number of ventilators is less than 5 times / h, the energy saving effect is very significant.

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Energy Saving and Low-Cost-Oriented Design Processes of Blank’s Dimensions Based on Multi-Objective Optimization Model

Processes ◽

10.3390/pr7110811 ◽

2019 ◽

Vol 7 (11) ◽

pp. 811 ◽

Cited By ~ 1

Author(s):

Yongmao Xiao ◽

Qingshan Gong ◽

Xiaowu Chen

Keyword(s):

Energy Consumption ◽

Energy Saving ◽

Optimization Model ◽

Low Cost ◽

Minimum Cost ◽

Processing Parameters ◽

Multi Objective Optimization ◽

Nsga Ii ◽

Multi Objective ◽

Set Up

The blank’s dimensions are an important focus of blank design as they largely determine the energy consumption and cost of manufacturing and further processing the blank. To achieve energy saving and low cost during the optimization of blank dimensions design, we established energy consumption and cost objectives in the manufacturing and further processing of blanks by optimizing the parameters. As objectives, we selected the blank’s production and further processing parameters as optimization variables to minimize energy consumption and cost, then set up a multi-objective optimization model. The optimal blank dimension was back calculated using the parameters of the minimum processing energy consumption and minimum cost state, and the model was optimized using the non-dominated genetic algorithm-II (NSGA-II). The effect of designing blank dimension in saving energy and costs is obvious compared with the existing methods.

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