Automation of Ac System Employing Plc and Scada

Automation of Ac System Employing Plc and Scada

Mohammed Rafeeq Asif Afzal*

P.A. College of Engineering, Visvesvaraya Technological University, Belagavi, Mangalore 574153, India

Corresponding Author Email: 
asif.afzal86@gmail.com
Page: 
8-16
|
DOI: 
https://doi.org/10.18280/ama_c.730102
Received: 
27 March 2018
|
Accepted: 
20 April 2018
|
Published: 
31 March 2018
| Citation

OPEN ACCESS

Abstract: 

Air conditioners have become an important need in industrial and domestic places. On the other hand industrial automation tools provide a wide range of applications in control and monitoring of mechanical, power, automobile, telecommunication systems etc. Programmable Logic Controller (PLC) and Supervisory Control and Data Acquisition (SCADA) can be easily used as automation tool in HVAC industries. In this work we present the monitoring and controlling of AC system employed for more prominent work space using PLC and SCADA.  PLC is used at the remote end as hardware to supervise and control the required air conditioning space. The ladder logic developed for programming PLC is provided which can also be implemented in monitoring and controlling of multiple AC systems in remote and local mode to operate either automatically or manually. SCADA is used to operate remotely by developing Graphical User Interface (GUI) using CIMPLICITY software. With all the features, this designed system is capable of efficient handling of the resources such as the compressor, blower, condenser etc. With all the levels of safety and durability, it maintains the temperature and control humidity levels within the official work place and also looks after the health of the compressor.

Keywords: 

AC system, SCADA, PLC, remote mode, local mode, manual mode, auto mode

1. Introduction
2. Design of the Automation System
3. Ladder Logic and Flow Diagram
4. Working and Implementation of the Designed System
5. Conclusion
  References

[1] Bi Q, Cai W, Wang Q, Hang C, Lee E. (2000). Advanced controller auto-tuning and its application in HVAC systems. Control Eng Pract 8: 633-44.

[2] Lin P, Broberg H. (2002). Internet-based monitoring and controls for HVAC applications. IEEE Ind Appl Mag 8: 49-54.

[3] Salsbury T. (2005). A survey of control technologies in the building automation industry. IFAC Proc. 38: 90-100.

[4] Zibin N, Zmeureanu R, Love J. (2016). Automatic assisted calibration tool for coupling building automation system trend data with commissioning. Autom Constr 61: 124-33.

[5] Ahuja A. (2016). Integrated building systems engineering and automation. Integr Nat Technol Smart Cities, Springer Int Publ 2016: 179-188.

[6] Kastner W, Neugschwandtner G. (2005). Communication systems for building automation and control. Proc IEEE 93: 1178–203.

[7] Wang S, Ma Z. (2008). Supervisory and optimal control of building HVAC systems: a review. HVAC&R Res. 14: 3-32.

[8] Alphonsus E, Abdullah M. (2016). A review on the applications of programmable logic controllers (PLCs). Renew Sustain Energy 60: 1185–205.

[9] Panchal P, Mahesuria G, Panchal R, Patel R. (2016). Upgradation in SCADA and PLC of existing LN 2 control system for SST-1. Fusion Eng Des.

[10] Xiao F, Wang S. (2009). Progress and methodologies of lifecycle commissioning of HVAC systems to enhance building sustainability. Renew Sustain Energy Rev. 13: 1144–9.

[11] Ahmad M, Mourshed M, Yuce B, Rezgui Y. (2016). Computational intelligence techniques for HVAC systems: A review. Build Simulation, Tsinghua Univ Press, p. 9.

[12] Agarwal Y, Balaji B, Gupta R, Lyles J, Wei M. (2010). Occupancy-driven energy management for smart building automation. Proc. 2nd ACM Work. Embed. Sens. Syst. Energy-Efficiency Build pp. 1–6.

[13] Afzal A, Ansari Z, Faizabadi A, Ramis M. (2017). Parallelization strategies for computational fluid dynamics software: state of the art review. Arch Comput Methods Eng. 24: 337–63. http://link.springer.com/article/10.1007/s11831-016-9165-4.

[14] Pinto R, Afzal A, D’Souza L, Ansari Z, Mohammed Samee AD. (2017). Computational fluid dynamics in turbomachinery: a review of state of the art. Arch Comput Methods Eng. 24: 467–79. https://doi.org/10.1007/s1183.

[15] Pinto RN, Afzal A, Navaneeth IM, Ramis MK. (2016). Computational analysis of flow in turbines. Inven. Comput. Technol. (ICICT), Int. Conf., Coimbatore, India: IEEE (3): 1-5. 10.1109/INVENTIVE.2016.7830174.

[16] Ansari Z, Faizabadi AR, Afzal A. (2017). Fuzzy c-Least Medians clustering for discovery of web access patterns from web user sessions data. Intell Data Anal 21: 553–75. 10.3233/IDA-150489.

[17] Rafeeq M, Afzal A, Rajendra S. (2018). Remote supervision and control of air conditioning systems in different modes. J Inst Eng Ser C. https://doi.org/10.1007/s40032-017-0434-2.

[18] Liu X, Hu R, Song Y. (2017). Clutch displacement servo control in gear-shifting process of electric vehicles based on two-speed DCT. Adv. Model Anal. C 72: 140–55.

[19] Huang Y, Qiao Y. (2017). Artificial raindrop algorithm for optimal parameter preference in digital IIR filters. Adv. Model Anal. C 72: 114–39.