Design PID Controllers for the Air-Conditioning Process Using Genetic Algorithm

2020 ◽  
pp. 391-399
Author(s):  
Bin Hao ◽  
Yu Chao Sun ◽  
Qing Chun Zheng ◽  
Shi Yue Zhang
Keyword(s):  
Genetic Algorithm ◽  
Air Conditioning ◽  
Pid Controllers ◽  
Conditioning Process

New Designing Approaches for Quadcopter PID Controllers Using Reference Model and Genetic Algorithm Techniques

2017 ◽  
Vol 10 (3) ◽  
pp. 240 ◽  
Author(s):  
Imane Siti ◽  
Mostafa Mjahed ◽  
Hassan Ayad ◽  
Abdeljalil El Kari
Keyword(s):  
Genetic Algorithm ◽  
Reference Model ◽  
Pid Controllers

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.

Comparison of fractional and integer PID controllers tuned by genetic algorithm

2016 ◽  
Author(s):  
Felipe A. de Castro ◽  
Nemerson D. Bernardes ◽  
Marco A. de S. L. Cuadros ◽  
Gustavo M. de Almeida
Keyword(s):  
Genetic Algorithm ◽  
Pid Controllers

scholarly journals On the Energy Efficiency of Indoor Air Conditioning

2019 ◽  
Vol 62 (4) ◽  
pp. 325-340 ◽  
Author(s):  
S. N. Osipov ◽  
A. V. Zakharenko ◽  
E. M. Shirokova
Keyword(s):  
Energy Efficiency ◽  
Heat Exchange ◽  
Indoor Air ◽  
Air Conditioning ◽  
Large Scale ◽  
Well Being ◽  
Physiological Adaptation ◽  
Limited Area ◽  
Air Conditioner ◽  
Conditioning Process

The increase of average outdoor temperatures and their fluctuations over the past 20 years (as evidenced by the records of summer temperatures in our country) has significantly increased the need for air conditioning premises where people are present for a long time, especially when they are crowded (shops, entertainment halls, classrooms, etc.). The air conditioning process is quite energy-intensive, but the growth of well-being in many republics of the former USSR, as well as the increasing complexity of the physiological adaptation of the human body to rising outdoor temperatures make it possible (and at the same time necessary) to implement these systems on a large scale. It is important to take into account that electricity prices are currently maintained at a high level for homeowners, and in the coming years the prices will only grow. Therefore, the development of new ways of significant increase of the energy efficiency of the indoor air conditioning process is of a great interest. One of these methods is the use of laminar (or close to them) moving layers of conditioned air in a limited area of work or rest of people. Such a zone, about 1.0‒1.2 m height from a floor in each apartment is, e.g., living rooms (bedroom) in which standard temperature conditions are created by means of simple air supplying and air intake devices. In the case of sedentary work of people, the height of such a zone of conditioned air should be increased to 1.3‒1.5 m. It has already been established that the use of laminar (or close to them) air flows allows to reduce the power consumption by two or more times due to significantly reduced heat exchange with the surrounding heated surfaces. Besides, the simplicity of such systems ought to be noted. In particular, in conditions of modern systems of control and management of air conditioning, the "duties" of consumers include only the installation on the control device of the initial data relating directly to the required parameters of the microclimate. At the same time, it should be noted that there is currently no complete scientific and technical description of aerodynamic and heat exchange processes in the air conditioning zone. Even in modern conditions for countries with a sharply continental climate (Russia, Kazakhstan, etc.), the problem is the choice of the type of air conditioner for its effective use in hot periods of summer. In general, it can be noted that all the problems of energy-efficient use of air conditioners must find a comprehensive solution.

scholarly journals Heating, Ventilation, and Air Conditioning System Optimization Control Strategy Involving Fan Coil Unit Temperature Control

2019 ◽  
Vol 9 (11) ◽  
pp. 2391 ◽  
Author(s):  
Chang-Ming Lin ◽  
Hsin-Yu Liu ◽  
Ko-Ying Tseng ◽  
Sheng-Fuu Lin
Keyword(s):  
Genetic Algorithm ◽  
Energy Conservation ◽  
Temperature Control ◽  
Control Strategy ◽  
Air Conditioning ◽  
Minimum Energy ◽  
System Optimization ◽  
Hvac System ◽  
Minimum Energy Consumption ◽  
Optimization Control

The objective of this study was to develop a heating, ventilation, and air conditioning (HVAC) system optimization control strategy involving fan coil unit (FCU) temperature control for energy conservation in chilled water systems to enhance the operating efficiency of HVAC systems. The proposed control strategy involves three techniques, which are described as follows. The first technique is an algorithm for dynamic FCU temperature setting, which enables the FCU temperature to be set in accordance with changes in the outdoor temperature to satisfy the indoor thermal comfort for occupants. The second technique is an approach for determining the indoor cold air demand, which collects the set FCU temperature and converts it to the refrigeration ton required for the chilled water system; this serves as the control target for ensuring optimal HVAC operation. The third technique is a genetic algorithm for calculating the minimum energy consumption for an HVAC system. The genetic algorithm determines the pump operating frequency associated with minimum energy consumption per refrigeration ton to control energy conservation. To demonstrate the effectiveness of the proposed HVAC system optimization control strategy combining FCU temperature control, this study conducted a field experiment. The results revealed that the proposed strategy enabled an HVAC system to achieve 39.71% energy conservation compared with an HVAC system operating at full load.

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