Energy-saving design and operation strategy of air conditioning cold and heat source in ultra-low energy building

2014 ◽  
Author(s):  
H.X. Li ◽  
C.H. Cao ◽  
G.H. Feng ◽  
K.L. Huang ◽  
R. Zhang
Keyword(s):  
Heat Source ◽  
Energy Saving ◽  
Air Conditioning ◽  
Low Energy ◽  
Operation Strategy

A multi-objective optimization operation strategy for ice-storage air-conditioning system based on improved firefly algorithm

2021 ◽  
pp. 014362442110455
Author(s):  
Xinwei Zhou ◽  
Junqi Yu ◽  
Wanhu Zhang ◽  
Anjun Zhao ◽  
Min Zhou
Keyword(s):  
Energy Saving ◽  
Economic Benefit ◽  
Air Conditioning ◽  
Firefly Algorithm ◽  
Optimal Operation ◽  
Ice Storage ◽  
Operation Strategy ◽  
Multi Objective Optimization ◽  
Air Conditioning System ◽  
Improved Firefly Algorithm

Reasonable distribution of cooling load between chiller and ice tank is the key to realize the economical and energy-saving operation of ice-storage air-conditioning (ISAC) system. A multi-objective optimization model based on improved firefly algorithm (IFA) was established in this study to fully exploit the energy-saving potential and economic benefit of the ISAC system. The proposed model took the partial load rate of each chiller and the cooling ratio of the ice tank as optimization variables, and the lowest energy consumption loss rate and the lowest operating cost of the ISAC system were calculated. Chaotic logic self-mapping was used to initialize population to avoid falling into local optimum, and Cauchy mutation was used to increase the population’s diversity to improve the algorithm’s global search ability. The experimental results show that compared with the operation strategy based on constant proportion, particle swarm optimization (PSO) algorithm, and firefly algorithm (FA), the optimal operation strategy based on IFA can achieve more significant energy-saving and economic benefits. Meanwhile, the convergence accuracy and stability of the algorithm are significantly improved. Practical application: The optimized operation strategy of the ice-storage air-conditioning system can reduce energy loss and operating costs. The traditional operation strategies have the problems of low optimization precision and poor optimization effect. Therefore, this study presents an optimal operation strategy based on IFA. The convergence accuracy and stability of the algorithm are increased after the algorithm is improved. The operation strategy can get the maximum energy-saving effect and economic benefit of the ISAC system.

Cold and Heat Source Energy-Saving Reconstruction for Central Air-Conditioning System in a Research and Development Center of Shanghai

2011 ◽  
Vol 204-210 ◽  
pp. 327-331
Author(s):  
Jin Wang ◽  
Jing Jing Xin ◽  
You Tao Zhou ◽  
Xin Lin Li ◽  
Shu Sheng Li
Keyword(s):  
Energy Consumption ◽  
Heat Source ◽  
Research And Development ◽  
Energy Saving ◽  
Air Conditioning ◽  
Electric Energy ◽  
Air Conditioning System ◽  
Central Air Conditioning ◽  
One Year ◽  
Development Center

Central air-conditioning energy consumption accounts for a large proportion of the buildings. And cold and heat source energy consumption accounts for about two-thirds of central air-conditioning system. For a research and development center in Shanghai, because cold and heat source capacity largely surpasses the actual demand, we propose to combine with cold sources of the two buildings. We call it "two-in-one" reconstruction. When cooling load is small, we use cold source in one building to support the two buildings. After implementation, by return on investment analysis, the average electric energy-saving rate is 9.6%. Investment can be recovered within one year.

scholarly journals Analysis of the Energy Use in the Mexican Residential Sector by Using Two Approaches Regarding the Behavior of the Occupants

2018 ◽  
Vol 8 (11) ◽  
pp. 2136 ◽  
Author(s):  
Ivan Oropeza-Perez ◽  
Astrid Petzold-Rodriguez
Keyword(s):  
Sensitivity Analysis ◽  
Energy Saving ◽  
Air Conditioning ◽  
Energy Use ◽  
Energy Savings ◽  
Integrated Approach ◽  
Low Energy ◽  
Energy Devices ◽  
Residential Sector ◽  
Reliable Basis

An analysis of the energy use in the Mexican residential sector is carried out. To achieve this, two approaches are taken into account. The first one is the usage of low-energy devices, and the second one is the decrease of their time of use. These two approaches are considered in the calculation method with random values of power and time of usage. The energy activities are divided into air-conditioning, illumination & appliances, and refrigeration. After total annual use is validated with the actual values of energy use in 2015, a sensitivity analysis of the approaches used separately and together is carried out in order to determine the potential of energy saving. Thereby, it is found that the most influential parameter for energy saving is the extensive acquisition of more efficient technologies of illumination & appliances, followed by the decrease of use of the same illumination & appliances. Furthermore, with an integrated approach that takes into account both the use of efficient devices and the reduction of their use for the three energy activities, a maximum of 19.67 TWh is calculated in 2015 for the Mexican residential sector. This approach is therefore expected to have a reliable basis for the development and improvement of policies that help to drive energy savings in an extensive manner in Mexico.

Efficient Concept of Low Energy Building

2005 ◽  
Author(s):  
Mahmoud A. Hassan
Keyword(s):  
Energy Consumption ◽  
Thermal Comfort ◽  
Energy Saving ◽  
Energy Efficient ◽  
Air Conditioning ◽  
Natural Ventilation ◽  
Building Materials ◽  
Building Design ◽  
Building Energy ◽  
Low Energy

Low energy architect is a major target of building researchers and designers worldwide. Obviously, any portion of energy that can be saved in this respect can be directed to industrial processes, if any. Building energy consumption can be reduced through various systems such as air conditioning (a major building energy consumer), lighting, equipment, etc. In regions where energy is limited or scarce, air conditioning would have to be replaced by natural ventilation for the removal of the building heat load for thermal comfort. Also, energy conservation issues are being more important in hot arid regions, especially because the building are consuming more than 60% of electric energy generated and about 65% of this energy is consumed for cooling. There is a set of complex factors, which determine energy needs in building, such as solar radiation, type of A/C systems, building operation, thermal properties of the building envelop... etc. In the present decade the aim is to discuss the advantage of energy efficient building design. There is several ways to reduce the energy consumed for the human comfort process, but what is the most energy efficient or more energy saving from these ways. One of these is the insulation, which can be used for insulating the wall and the roof, which subjected to the large amount of the solar heat gain. The insulation of the roof is intended to maximize resident’s thermal comfort and minimize energy consumption of housing. The parameters, which are effect on the thermal performance of the roof, are the color, general construction, insulation and ventilation. This paper present the effect of insulation of the roof on the amount of energy consumed for different types of insulation in order to select the suitable insulation which give the minimum cost and maximum energy saving. This work was done using an energy software program (Visual DOE). This paper provided suggestions to improve the building construction for the thermal comfort. A parametric analysis was investigated for the economic analysis of various insulating building materials.

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

Energies ◽  
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.

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.

scholarly journals Energy-saving diagnosis model of central air-conditioning refrigeration system in large shopping mall

2021 ◽  
Vol 7 ◽  
pp. 4035-4046
Author(s):  
Wenqiang Jing ◽  
Junqi Yu ◽  
Wei Luo ◽  
Chujun Li ◽  
XinYi Liu
Keyword(s):  
Energy Saving ◽  
Air Conditioning ◽  
Shopping Mall ◽  
Refrigeration System ◽  
Central Air Conditioning ◽  
Diagnosis Model
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