scholarly journals Climate Compensation and Indoor Temperature Optimal Measuring Point Energy Saving Control in VAV Air-Conditioning System

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4398 ◽  
Author(s):  
Xiuying Yan ◽  
Cong Liu ◽  
Meili Li ◽  
Ating Hou ◽  
Kaixing Fan ◽  
...  
Keyword(s):  
Energy Saving ◽  
Air Temperature ◽  
Control Strategy ◽  
Air Conditioning ◽  
Compensation Scheme ◽  
Indoor Temperature ◽  
Air Conditioning System ◽  
Measuring Point ◽  
Temperature Measuring ◽  
Environment Control

Temperature measuring point is the key to room environment control. Temperature measuring points and climate changes are directly related to the room control effect. It is of great theoretical and practical significance to study the temperature measuring points and control strategy based on climate compensation. In this study, first, the climate compensation concept in a heating system was introduced into a variable air volume (VAV) air-conditioning system. The heating load was modeled as a function of supply air temperature by analyzing the heat exchange. Based on each control link of subsystems, a climate compensation scheme is proposed to determine the optimal set-point of the supply air temperature. At the same time, a layout of multiple temperature measuring points of an air-conditioned room was studied. Furthermore, the optimal indoor temperature measuring point was determined using an adaptive weighted fusion method. Finally, simulation results show that the proposed method has better control effects on indoor temperature adjustment compared with the traditional method. The optimal supply air temperature in summer and winter was determined according to the proposed climate compensation scheme, and the supply air temperature was controlled using an improved single-neuron adaptive control strategy. Experimental results show that the maximum energy saving can reach up to 35.5% in winter and 6.1% in summer.

Energy Conservation Analysis for Air Conditioning System in Rail Transit Stations

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.

scholarly journals Research on Comprehensive Energy Saving Control Strategy of Air Conditioning

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.

scholarly journals Multi-Objective Optimization of Energy Saving Control for Air Conditioning System in Data Center

Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1474 ◽  
Author(s):  
Leehter Yao ◽  
Jin-Hao Huang
Keyword(s):  
Energy Saving ◽  
Air Temperature ◽  
Data Center ◽  
Air Conditioning ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Air Conditioning System ◽  
Multi Objective ◽  
Control Scheme ◽  
Energy Saving Control

A multi-objective optimization scheme is proposed to save energy for a data center air conditioning system (ACS). Since the air handling units (AHU) and chillers are the most energy consuming facilities, the proposed energy saving control scheme aims to maximize the saved energy for these two facilities. However, the rack intake air temperature tends to increase if the energy saving control scheme applied to AHU and chillers is conducted inappropriately. Both ACS energy consumption and rack intake air temperature stabilization are set as two objectives for multi-objective optimization. The non-dominated sorting genetic algorithm II (NSGA-II) is utilized to solve the multi-objective optimization problem. In order for the NSGA-II to evaluate fitness functions that are both the ACS total power consumption and AHU outlet cold air temperature deviations from a specified range, neural network models are utilized. Feedforward neural networks are utilized to learn the power consumption models for both chillers and AHUs as well as the AHU outlet cold air temperature based on the recorded data collected in the field. The effectiveness and efficiency of the proposed energy saving control scheme is verified through practical experiments conducted on a campus data center ACS.

Individual Thermal Environments of Building with a Novel Air-Conditioning Energy-Saving Equipment

2013 ◽  
Vol 368-370 ◽  
pp. 645-648
Author(s):  
Nguyen Anh Tuan ◽  
Wu Chieh Wu ◽  
Huy Bich Nguyen
Keyword(s):  
Energy Saving ◽  
Air Conditioning ◽  
Thermal Environment ◽  
Air Conditioning System ◽  
Outlet Port ◽  
3 Dimensional ◽  
Thermal Environments ◽  
Energy Saving Potential ◽  
Environment Control ◽  
Port Opening

Individual air-conditioning system (IACS) can create an individual thermal environment control in a workroom which can contribute to save air-conditioning energy. In this study, we analyze the airflow circulation cell of the IACS with varied outlet port opening dimensions using the computational fluid dynamics (CFD) technique. We created an IACS, two workstations, lightings, and a cabinet in a 3-dimensional room. The fluid was assumed to be Newtonian, unsteady, and incompressible. We examined the effects of the outlet port opening on airflow circulation establishing process. Results will indicate the suitable outlet port opening for maintaining individual satisfied occupants’ requirements and improving energy saving potential.

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

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.

scholarly journals Assessing a Multi-Objective Genetic Algorithm with a Simulated Environment for Energy-Saving of Air Conditioning Systems with User Preferences

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 344
Author(s):  
Alejandro Humberto García Ruiz ◽  
Salvador Ibarra Martínez ◽  
José Antonio Castán Rocha ◽  
Jesús David Terán Villanueva ◽  
Julio Laria Menchaca ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Energy Saving ◽  
User Satisfaction ◽  
Air Conditioning ◽  
State Of The Art ◽  
User Preferences ◽  
The State ◽  
Nsga Ii ◽  
Air Conditioning System

Electricity is one of the most important resources for the growth and sustainability of the population. This paper assesses the energy consumption and user satisfaction of a simulated air conditioning system controlled with two different optimization algorithms. The algorithms are a genetic algorithm (GA), implemented from the state of the art, and a non-dominated sorting genetic algorithm II (NSGA II) proposed in this paper; these algorithms control an air conditioning system considering user preferences. It is worth noting that we made several modifications to the objective function’s definition to make it more robust. The energy-saving optimization is essential to reduce CO2 emissions and economic costs; on the other hand, it is desirable for the user to feel comfortable, yet it will entail a higher energy consumption. Thus, we integrate user preferences with energy-saving on a single weighted function and a Pareto bi-objective problem to increase user satisfaction and decrease electrical energy consumption. To assess the experimentation, we constructed a simulator by training a backpropagation neural network with real data from a laboratory’s air conditioning system. According to the results, we conclude that NSGA II provides better results than the state of the art (GA) regarding user preferences and energy-saving.

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