Air Conditioning Control System Research Articles

Heat and humidity features and energy saving potential of temperature and humidity independent control air-conditioning system using refrigerant mixture

Heat and humidity features and energy saving potential of temperature and humidity independent control air-conditioning system using refrigerant mixture

Performance analysis and evaluation of desiccant air-handling unit under various operation condition through measurement and simulation in hot and humid climate

In hot and humid climate such as in Japan and south east Asia, dehumidification in summer is really important for air conditioning. Temperature and humidity independent control (THIC) of air conditioning system can handle sensible heat and latent heat separately, and provide good indoor environment and achieve energy conservation. Desiccant air handling unit is one of the major solution for THIC of air conditioning system. It needs hot water to regenerate sorbent which absorbs moist in the air. Combined heat and power can supply hot water at almost constant temperature for desiccant air handling system and also contribute to the business continuity plan of commercial buildings. However, there are still uncertainties about the factors which affect energy performance of desiccant air handling unit and the optimum design and operations in hot and humid climate. The objectives of this paper are to prove factors which affect energy performance of desiccant air handling unit by measurement analysis and show optimum condition of the desiccant air handling unit under various room conditions by simulation. Measurement analysis shows that energy performance of desiccant air handling unit depends not only on the inlet air condition to dehumidification wheel but also on designed supply air humidity. Furthermore, simulation results show the optimum inlet air condition entering dehumidification wheel under various supply air absolute humidity which is determined by design room conditions. These results provide useful information of desiccant air handling unit during design and operation phase of buildings in hot and humid climate.

Discussion on fresh air volume in Temperature and Humidity Independent Control of Air-conditioning System

The fresh air volume in Temperature and Humidity Independent Control of Air-conditioning System(THIC) of a typical office was comfirmed, under the premise of adopting the refrigeration dehumidifying fresh air unit(7°C/12°C). By detailed calculating the space moisture load and the fresh air volume required for dehumidification in 120 selected major cities in China, it can be inferred that the minimum fresh air volume required for dehumidification in THIC is mainly determined by the local outdoor air moisture and the outdoor wind speed; Then the mathematical fitting software Matlab was used to fit the three parameters, and a simplified formula for calculating the minimum per capita fresh air volume required for dehumidification was obtained; And the indoor relative humidity was simulated by the numerical software Airpak and the results by using the formula data and the data for hygiene were compared to verify the relibility of the simplified formula.

Event-driven optimal control of central air-conditioning systems: Event-space establishment

Real-time optimal control is widely adopted in central air-conditioning systems to improve the building energy management efficiency by adjusting system controllable variables according to system operating conditions. In time-driven optimal control, optimization actions are triggered periodically, which may not be efficient when the operating conditions of central air-conditioning systems are significantly irregular. To overcome this limitation, event-driven optimal control was proposed, in which optimization actions are triggered by “events” instead of a “clock”. In event-driven optimal control, the definition of events are critical because “events” will directly affect the control efficiency and the online computational efficiency. In current literature, however, very few studies can be found on how to systematically establish a suitable event space for air-conditioning systems. This paper therefore presents a knowledge-based method for establishing event space. Case studies that were carried out in a typical commercial air-conditioning system is used to demonstrate the proposed method and its effectiveness, where real measured load and weather data were used.

IGRM

Occupancy detection is one of the many applications of Building Automation Systems (BAS) or Heating, Ventilation, and Air Conditioning (HVAC) control systems, especially, with the rising demand of Internet of Things (IoT) services. This article describes the fusion of data collected from sensors by exploiting their potential to sense occupancy in a room. For this purpose, a sensor test bed is deployed that includes four sensors measuring temperature, relative humidity, distance from the first obstacle, and light along with a Arduino micro-controller to validate our model. In addition, this article proposes three algorithms for efficient fusion of the sensor data that is inspired by the Grey theory. An improved Grey Relational Model (iGRM) is proposed, which acts as the base classifier for the other two algorithms, namely, Grey Relational Model with Bagging (iGRM-BG) and Grey Relational Model with Boosting (iGRM-BT). Furthermore, all three algorithms use a sliding window concept, where only the samples inside the window participate in model training. Also, we have considered varying number of window size for optimal comparison. The algorithms were tested against the experimental data collected through a test bed as well as on a publicly available large dataset, where both the ensemble models, iGRM-BG and iGRM-BT, are seen to enhance the performance of iGRM. The results reveal exceptionally high performances with accuracies above 95% (iGRM) and up to 100% (iGRM-BT) for the experimental dataset and above 98.24% (iGRM) and up to 99.49% (iGRM-BG) using the publicly available dataset. Among the three proposed models, iGRM-BG was observed to outperform both iGRM and iGRM-BT owing to its advantage of being an ensemble model and its robustness against over-fitting.

Modeling occupancy distribution in large spaces with multi-feature classification algorithm

Occupancy information enables robust and flexible control of heating, ventilation, and air-conditioning (HVAC) systems in buildings. In large spaces, multiple HVAC terminals are typically installed to provide cooperative services for different thermal zones, and the occupancy information determines the cooperation among terminals. However, a person count at room-level does not adequately optimize HVAC system operation due to the movement of occupants within the room that creates uneven load distribution. Without accurate knowledge of the occupants' spatial distribution, the uneven distribution of occupants often results in under-cooling/heating or over-cooling/heating in some thermal zones. Therefore, the lack of high-resolution occupancy distribution is often perceived as a bottleneck for future improvements to HVAC operation efficiency. To fill this gap, this study proposes a multi-feature k-Nearest-Neighbors (k-NN) classification algorithm to extract occupancy distribution through reliable, low-cost Bluetooth Low Energy (BLE) networks. An on-site experiment was conducted in a typical office of an institutional building to demonstrate the proposed methods, and the experiment outcomes of three case studies were examined to validate detection accuracy. One method based on City Block Distance (CBD) was used to measure the distance between detected occupancy distribution and ground truth and assess the results of occupancy distribution. The results show the accuracy when CBD = 1 is over 71.4% and the accuracy when CBD = 2 can reach up to 92.9%.

Developed adaptive neuro-fuzzy algorithm to control air conditioning system at different pressures

The paper developed artificial intelligence technique adaptive neuro-fuzzy controller for air conditioning systems at different pressures. The first order Sugeno fuzzy inference system was implemented and utilized for modeling and controller design. In addition, the estimation of the heat transfer rate and water mass flow rate in/out the system was determined by fuzzy IF-THEN rules. The combination between back propagation algorithm and least square method helps to optimize the membership functions and generated the fuzzy rules that describe the relationship between the input/output data of the air conditioning system which changes with pressure values. The fuzzy rules are tuned by adaptive neural fuzzy inference system ANFIS. Statistical indices such as Root Mean Square Error (RMSE) and mean relative error (MRE) are used to evaluate performance of the ANFIS model. The values of the indices show that ANFIS model can accurately and reliably be used to air conditioning system and the simulated model of the system shows a good performance results.Keywords: fuzzy logic, adaptive fuzzy, air conditioning system, Intelligent control

FUZZY LOGIC CONTROL OF AIR-CONDITIONING SYSTEM IN LECTURER ROOM OF STMIK INDONESIA PADANG

Abstract. The research on Fuzzy logic control of air-conditioning system in lecturer room of STMIK Indonesia Padang has been done. AC is a system or machine designed to stabilize the air temperature and humidity of an area used for cooling or heating depending on the nature of air at certain time. Commonly the AC uses a refrigeration cycle but sometimes uses evaporation. Lecturer room of STMIK Indonesia Padang has a size of 120 m 2 and consists of 32 rooms. For the convenience of lecturers activity, the room is equipped by three AC each of 3 PK. The room has problems in determining the right size in the AC setting, sometimes the air temperature in the room is too cold or too hot. There are many activities conducted in the lecturer room, in the form of providing excellent service to students, such as thesis supervision, practical work, and discussion activities. With the number of lecturers in the room that is as many as 32 people and each serves about five to ten students daily then the room temperature sometimes becomes unstable. Based on the results of the study, with the room size of 120 m 2 and the number of person as many as 100 people using three AC (each with 3 PK capacity) so the appropriate temperature is at position 18.0 oC. Keywords: Air Conditioner, Fuzzy Logic, and Temperature

Remote Supervision and Control of Air Conditioning Systems in Different Modes

In the era of automation, most of the application of engineering and science are interrelated with system for optimal operation. To get the efficient result of an operation and desired response, interconnected systems should be controlled by directing, regulating and commanding. Here, air conditioning (AC) system is considered for experimentation, to supervise and control its functioning in both, automated and manual mode. This paper reports the work intended to design and develop an automated and manual AC system working in remote and local mode, to increase the level of comfort, easy operation, reducing human intervention and faults occurring in the system. The Programmable Logical Controller (PLC) and Supervisory Control and Data Acquisition (SCADA) system were used for remote supervision and monitoring of AC systems using series ninety protocol and remote terminal unit modbus protocol as communication module to operate in remote mode. PLC was used as remote terminal for continuous supervision and control of AC system. SCADA software was used as a tool for designing user friendly graphical user interface. The proposed SCADA AC system successfully monitors and controls in accordance within the parameter limits like temperature, pressure, humidity and voltage. With all the features, this designed system is capable of efficient handling of the resources like the compressor, humidifier etc., with all the levels of safety and durability. This system also maintains the temperature and controls the humidity of the remote location and also looks after the health of the compressor.

基于多目标规划的中央空调系统优化控制研究

为了提高中央空调系统的工作效率，同时降低能源消耗，需要对中央空调系统进行节能优化控制研究。现有的中央空调系统控制策略很难实现实时控制，且优化控制效果较差。为此，提出了基于多目标规划的中央空调系统动态优化方法。该方法先研究了中央空调系统各变量的变化规律，并对数据进行降维；然后，使用多元回归分析方法得到变量的回归方程；在此基础上，以设备运行状态和转速为决策变量，以系统总耗电量和系统效率为目标函数，在设备转速、状态、系统稳定性和设备运转等约束条件下，建立了基于多目标规划的中央空调系统动态优化模型。优化结果显示，所提方法优化控制效果较好，有效地降低了系统总耗电量。 In order to improve the efficiency of central air conditioning system and reduce energy consump-tion, it is necessary to study the energy-saving optimization control of the central air conditioning system. However, the current control strategy of central air conditioning system is difficult to realize real-time control, and has the problem of poor optimization control. Therefore, we propose an optimization control method for central air conditioning system based on multi-objective programming. Firstly, we study the changing rules of the variables in the central air conditioning system, and reduce the dimension of the data. Then, we used the multiple regression analysis to obtain the regression equation of the variable. On the basis of the above, we use the operating condition and speed of the equipment as the decision variables, and take the total energy con-sumption and the system efficiency as the objective function. Under the constraints of equipment speed, state, system stability and equipment operation, we establish the optimization control model of the central air conditioning system based on the multi-objective programming model. Finally, the optimization result shows that the optimized control effect of our proposed method is better, and it can effectively reduce the total power consumption.

Prediction of Indoor Temperature and Relative Humidity Based on Cloud Database by Using an Improved BP Neural Network in Chongqing

For continuous improvement of productivity, accurate, stable, and reliable control of temperature and humidity is important in industrial production. Accurate prediction of air temperature and humidity can improve the predictability and stability of air conditioning control systems. In this paper, based on the cloud database of industry settings, an improved prediction model based on backpropagation (BP) neural networks was established to forecast indoor air temperature (IT) and relative humidity (IH) every 10 min and 6–72 h in advance. The experimental building was in Chongqing, a typical humid, hot-summer, and cold-winter area in China. The test data were used to determine the optimal parameters of the neural network model. The experimental results showed that the IT and IH predictions by our model have strong correlations with the actual data, with the coefficients of determination being 0.9897 and 0.9778, respectively. Compared with other literature, our model was more effective in temperature prediction. The presented method can be used for the prediction and control of the indoor temperature and relative humidity in industrial production.

The synthesis procedure of multidimensional regulator for precision air conditioner with steam humidifier

The automatic control system (ACS) of air conditioning is considered in the framework of the unified computer-integrated complex with technological links of the air conditioner equipment. Taking into account the availability of dynamic models of HVAC equipment in the state space (developed by the authors in the previous works) precision air conditioner complex mathematical model with steam humidifier for the stabilization of microclimate parameters in the premises is obtained considering the technological relations between the climatic equipments.The dynamic model differs from the existing one by technological linkages due to sequential treatment of the supply air for the HVAC equipment and the use of moisture content parameter (instead of relative humidity) for mass transfer modeling in the process of air preparation. The procedure of optimal multivariate linear-quadratic digital controller (LQDC) in the state space, which takes into account the logical switching in HVAC equipment operation for the modified control algorithm by the “optimum mode” method, is offered. Simulation of transient processes for the ACS of precision air conditioning has confirmed the effectiveness of the proposed procedure of multidimensional control synthesis. Additional condition is the usability of the obtained model in the MatLAB environment.The ACS use with LQDC improves the integral quality indicators by 1.2 – 2.3 times in comparison with the ACS which uses one-dimensional digital controllers, and also decreases the colunt and duration of the transient processes. This approach allows us to rethink the synthesis of ACS air conditioning on the basis of differentiation of the mutual influence of governing parameters and it enables the transferring of the air conditioning control system to the qualitatively new level and provides the effective use of energy for artificial microclimate systems.

On optimization of thermal sensation satisfaction rate and energy efficiency of public rooms: A case study

For sustainability, many studies have been conducted on energy saving for HVAC (heating, ventilation, and air-conditioning) systems. In a public place, different persons may have different thermal comfort requirements. Few studies are done so far for energy saving in a public place with HVAC systems that can accommodate many persons with thermal sensation differences for different persons being taken into account. In this work, during the summer from May to September in 2016, an investigation for energy saving is done in a large library room at Macau University of Science and Technology, Macau, China. In such a large room, the temperature in different areas is different and many students with different thermal sensations study in the room at the same time. Under such an environment, to save energy as well as maximize the total thermal satisfactory rate, a large number of experiments are carried out. Based on the collected data, methods are given to predict the indoor temperature for each reading area and thermal satisfactory rate under the current indoor temperature. Then, an efficient algorithm is developed to maximize the thermal satisfactory rate for the entire room by optimizing the input temperature of the ACC (air-conditioning control) system such that energy can be saved. Results show that, under the worst situation, by comparing with the manual control, the daily electricity saving is about 93 kWh and the electricity saving during the period from May to September is about 13,950 kWh.

再生可能エネルギーとコージェネレーションを利用した潜熱・顕熱分離空調方式に関する研究 （第4報）LCEMツールを活用したデシカント空調機のモデル化と予冷コイル出口温度設定条件によるケーススタディ

再生可能エネルギーとコージェネレーションを利用した潜熱・顕熱分離空調方式に関する研究 （第4報）LCEMツールを活用したデシカント空調機のモデル化と予冷コイル出口温度設定条件によるケーススタディ

再生可能エネルギーとコージェネレーションを利用した潜熱・顕熱分離空調方式に関する研究 （第3報）デシカント外調機の運転実績と性能評価

再生可能エネルギーとコージェネレーションを利用した潜熱・顕熱分離空調方式に関する研究 （第3報）デシカント外調機の運転実績と性能評価

在室者の調整行動を利用したアクティブ省エネ空調制御システムの研究 その3.冬期における室内温熱環境の実測とアンケート調査

在室者の調整行動を利用したアクティブ省エネ空調制御システムの研究 その3.冬期における室内温熱環境の実測とアンケート調査

An advanced simulation test bed for the stability analysis of variable air volume air-conditioning control system. Part 1: Optimal simplified model of building envelope for room thermal performance prediction

This paper and its future companion papers, were aimed to develop a set of efficient and accurate enough modular tools to build a simulation test bed for the stability analysis of interacting VAV (variable air volume air-conditioning system) control loops. By providing the correlation equations between the heat flow and temperature of the two opposite surfaces, the wall model was expected to link adjacent zones effectively and efficiently. In part 1, the development of an optimal simplified 3R2C (composed of three resistances and two capacitances) thermal network model of building envelope, i.e., the wall model, was descripted. The verification showed that the simplification of one-dimensional heat conduction through a typical wall of heavy construction was acceptable. The accuracy of the optimal simplified 3R2Cmodel was satisfying, and outperformed that of the optimal 4R3C model as well as two 3R2C models which were normally used in practical applications. First and foremost, the room dimensions of the test bed with the boundary conditions in numerical scheme were designed under the principle of similarity. After validation of the numerical scheme with the high-cited scaled experiment, a series of numerical test cases simulating the potential oscillations in practical applications, were conducted. Then, the long neglected concerned frequency range within which heat flow transfer through extern wall, was determined. Finally, the part of solid wall was separated with the part of indoor air, and was developed into a flexible wall module of 3R2C model based on frequency domain regression.

A general approach for mixed-integer predictive control of HVAC systems using MILP

Abstract The topic of the paper is optimal control of heating, ventilation, and air conditioning (HVAC) systems. Using mixed-integer linear programming (MILP) the main contribution is a flexible and modular MILP model of HVACs. It is the centerpiece of the proposed hierarchical multi-input multi-output (MIMO) model predictive control (MPC) framework for energy, comfort, and wear optimization. On the upper-level a plant MPC takes care of the slow dynamics of a plant. On the lower-level a MILP-MPC based on a MILP optimization model of an HVAC system optimizes the HVAC operation. The MILP-MPC considers the first few samples of the control trajectory of the plant MPC as its reference trajectory. It minimizes power consumption and switching of the HVAC. Thereby it has to obey constraints, consider component characteristics by nonlinearity approximation, and solve a unit commitment problem. The fact that the plant MPC can be based on an almost arbitrary plant model and the MILP model of the MILP-MPC can represent a variety of different HVAC systems unifies HVAC control. Features and results are presented in case studies: The first case study shows that state of the art HVAC operation is outperformed even if the predictive capability is not used. The second case study demonstrates that temperature, CO2 level, and humidity can be controlled simultaneously in a decoupled fashion. The third case study reveals that if also the lower-level MILP-MPC oversees the latency periods of HVAC components optimal switching is achieved.

Comparative Study on Implementing Home Air Conditioning for Passenger Carriages in the Indonesian Railway

Passenger comfort is important in railway transport system. The train operator company in Indonesia would like to increase passenger comfort by installing home air conditioning into all existing carriages of the economy train. The air conditioning is expected to give better passenger convince. Therefore, the aims of this research are to know the cooling load and compare characteristic between home Air Conditioning (AC) and train AC. The cooling load calculation is analyzed using Cooling Load Temperature Difference (CLTD)/Solar Cooling Load (SCL)/Cooling Load Factor (CLF) method. Comparison between both home air conditioning and train air conditioning are discussed to identify the benefits and drawbacks of each type. The total heat that needs to be removed from a passenger carriage with home AC is 104,334 Btu/h, while the total cooling capacity of home AC is 75,000 Btu/h. The passenger carriages with train AC have cooling capacity 119,100 Btu/h to remove heat 11,5290 Btu/h. The Energy Efficiency Ratio (EER) value of most home AC is higher than train AC, installation time of home AC is shorter than train AC, total cost for 20 years period of home AC is more than train AC. There is no guarantee for home AC, so everything that happens to it will become the full responsibility of train operator company. The train AC control system is more effective than the home AC. No fresh air is permitted to circulate within the home AC system hence, the same air is repeatedly processed in the system. Implementing home air conditioning in the existing passenger carriages is worthwhile for short time period in the goal to increase and improve the level of service provided by giving better comfortability to the passenger.

冷房発停にマルコフモデルを適用した場合の熱負荷特性に関する基礎的検討 : 第3報-実測に基づく冷房発停状態の遷移特性に関する考察

冷房発停にマルコフモデルを適用した場合の熱負荷特性に関する基礎的検討 : 第3報-実測に基づく冷房発停状態の遷移特性に関する考察