PID Controller for Optimum Energy Efficiency in Air-Conditioner
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Air conditioning is a process of excluding moisture and heat in interior space for better thermal comfort. It is also one of the largest energy consumers in a household. The air-conditioner uses a lot of energy to maintain desired room temperature. The world is getting old and technologies are getting more advanced every day, energy-efficient appliances are needed to preserve the world. This paper presents a design and testing of the PID control for temperature and humidity control using Arduino to get the optimum energy efficiency. The system was developing by implementing the DHT22 sensor. The objectives of this work are; to design experimental model of air conditioning system, and to optimize the system using PID control. The Arduino is used in this work to showcase the temperature and humidity reading. The experimental model has been successfully built for use with PC fan with 12V and 0.26A current rate. The real-life performance is quite satisfactory.
 Dounis, A. I. and C. Caraiscos, "Advanced control systems engineering for energy and comfort management in a building environment—A review." Renewable and Sustainable Energy Reviews 13(6-7): 1246-1261, 2009.
 Fayazbakhsh, M. A., et al, "Gray-box model for energy-efficient selection of set point hysteresis in heating, ventilation, air conditioning, and refrigeration controllers." Energy Conversion and Management 103: 459-467, 2015.
 Mohammed, J. A.-K., et al, "Investigation of high performance split air conditioning system by using Hybrid PID controller." Applied Thermal Engineering 129: 1240-1251, 2018.
 Moradi, H., et al, "PID-Fuzzy control of air handling units in the presence of uncertainty." International Journal of Thermal Sciences 109: 123-135, 2016.
 Soyguder, S. and H. Alli, "An expert system for the humidity and temperature control in HVAC systems using ANFIS and optimization with Fuzzy Modeling Approach." Energy and Buildings 41(8): 814-822, 2009.
 Soyguder, S. and H. Alli, "Predicting of fan speed for energy saving in HVAC system based on adaptive network based fuzzy inference system." Expert Systems with Applications 36(4): 8631-8638, 2009.
 Tang, R., et al, "Optimal control strategy of central air-conditioning systems of buildings at morning start period for enhanced energy efficiency and peak demand limiting." Energy 151: 771-781, 2018.
 Tang, R., et al, "A direct load control strategy of centralized air-conditioning systems for building fast demand response to urgent requests of smart grids." Automation in Construction 87: 74-83, 2018.
 Ulpiani, G., et al, "Comparing the performance of on/off, PID and fuzzy controllers applied to the heating system of an energy-efficient building." Energy and Buildings 116: 1-17, 2016.
 Wang, H., et al, "Modeling of a hybrid ejector air conditioning system using artificial neural networks." Energy Conversion and Management 127: 11-24, 2016.
 Wang, H. and Y. Chen, "A robust fault detection and diagnosis strategy for multiple faults of VAV air handling units." Energy and Buildings 127: 442-451, 2016.
 Wang, X., et al, "On optimization of thermal sensation satisfaction rate and energy efficiency of public rooms: A case study." Journal of Cleaner Production 176: 990-998, 2018.
 Wang, Y., et al, "Monitoring and autonomous control of Beijing Subway HVAC system for energy sustainability." Energy for Sustainable Development 39: 1-12, 2017.
 Wemhoff, A. P, "Calibration of HVAC equipment PID coefficients for energy conservation." Energy and Buildings 45: 60-66, 2012.
 Xu, X., et al, "A control-oriented hybrid model for a direct expansion air conditioning system." Energy and Buildings 155: 76-87, 2017.
 Yabanova, İ. and A. Keçebaş, "Development of ANN model for geothermal district heating system and a novel PID-based control strategy." Applied Thermal Engineering 51(1-2): 908-916, 2013.
 Yan, M., et al, "Model Predictive Control of the Air-conditioning System for Electric Bus." Energy Procedia 105: 2415-2421, 2017.
 Zhong, Z., et al, "Simulation Based Control Performance Evaluation of a Novel Fuzzy Logic Control Algorithm for Simultaneously Controlling Indoor Air Temperature and Humidity Using a Direct Expansion (DX) Air conditioning (AC) System”, 2017.
 Zucker, G., et al, "A ventilation system controller based on pressure-drop and CO 2 models." Energy and Buildings 155: 378-389, 2017.
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