i-manager Publications

i-manager's Journal on Instrumentation and Control Engineering (JIC)

Current Issue Vol. 11 Issue 2

Neural Network-Based Monitoring of Critical Parameters in Drinking Water for Enhanced Quality Assurance
Monitoring and Improvement of PV Panel Efficiency Due to Thermal Effect
Model Predictive Control of a Serial Link Robot Manipulator
Direct Torque Control (DTC) and Three Phase Induction Motor Simulation in MATLAB/Simulink
IoT-Enabled Smart Water Tank Monitoring System with Android Application Control

Most Cited

Volume 5 Issue 3 May - July 2017

Research Paper

The Possibility of using ITAE Poles in Optimal MIMO Decentralized Control Systems

Ashraf M. Abdulhamed* , Ahmed A.M. El-Gaafary**

* Lecturer, Department of Communications and Electronics Engineering., College of Engineering, Umm Al-Qura University, Al-Lith Branch, KSA.

** Professor, Department of Electrical Engineering, Faculty of Engineering, Minia University, Egypt.

Abdulhamed. A.M., and El-Gaafary. A.A.M. (2017). The Possibility of using ITAE Poles in Optimal MIMO Decentralized Control Systems. i-manager’s Journal on Instrumentation and Control Engineering, 5(3), 1-9. https://doi.org/10.26634/jic.5.3.13677

Abstract

This study introduces the input decentralized control technique for a strongly coupled MIMO system in a simple and clear procedure through a numerical example based on a combination of both pole placement and linear quadratic regulator techniques. This system can be stabilized by a multilevel control, each decoupled subsystem can be stabilized separately by using local controllers, which can provide a desired degree of stability, while global controllers are applied to enhance the overall system stability through reducing the effect of the interconnections among subsystems. The possibility of using the predetermined ITAE poles at different frequency values is investigated, these pole locations may be deviated from its nominal placed values for each decoupled subsystem, which affect subsystem as well as overall system stability, or lead to a slow overall system eigenvalues. Linear, quadratic optimal technique can be applied over the subsystem level in order to shift the slowest obtained pole locations into a much more stable places, which in turn shift the slowest overall system eigenvalues and guarantee a higher stability degree. This procedure can be applied many times until all the undesired poles are shifted.

References

[1]. Alavian, A. & Rotkowitz, M. (2015, July). On the pole selection for 8 -optimal decentralized control. In American Control Conference (ACC), 2015 (pp. 5471- 5476). IEEE.

[2]. Chalupa, P. & Bobál, V. (n.d). Decentralized Control Of Multivariable System using Real Time Workshop. Department of Control Theory, Institute of Information Technologies, Tomas Bata University, Zlin.

[3]. Elizabeth, S. & Jothilakshmi, R. (2013). Observability and Controllability of MIMO Control Systems via Difference Equations. International Journal of Computer Applications, 62(1), 37-42.

[4]. Erol, H. E., & Iftar, A. (2017). Decentralized controller design by continuous pole placement for neutral timedelay systems. Transactions of the Institute of Measurement and Control, 39(3), 297-311.

[5]. Franklin, G. F., Powell, J. D., & Emami-Naeini, A. (2002). Feedback Control of Dynamic Systems. Prentice-Hall Inc.

[6]. Ghoreishi, S. A. & Nekoui, M. A. (2012). Optimal weighting matrices design for LQR controller based on genetic algorithm and PSO. In Advanced Materials Research (Vol. 433, pp. 7546-7553). Trans Tech Publications.

[7]. Kucera, V. (2011). Decoupling optimal controllers. In th Proc. 18 Internat. Conf. Process Control (pp. 400-407).

[8]. Kucera, V. & Cigler, J. (2010, March). Optimal control systems with prescribed eigenvalues. In Communications, th Control and Signal Processing (ISCCSP), 2010 4 International Symposium on (pp. 1-6). IEEE.

[9]. Labibi, B., Lohmann, B., Sedigh, A. K. & Maralani, P. J. (2000). Sufficient condition for stability of decentralised control. Electronics Letters, 36(6), 588-590.

[10]. Lavaei, J., & Aghdam, A. G. (2008, June). Decentralized pole assignment for interconnected systems. In American Control Conference, 2008 (pp. 3601-3607). IEEE.

[11]. Martins, F. G. (2005). Tuning PID controllers using the ITAE criterion. International Journal of Engineering Education, 21(5), 867.

[12]. Nath, V. & Mitra, R. (2014). Robust Pole Placement using Linear Quadratic Regulator Weight Selection Algorithm. International Journal of Scientific Research Engineering & Technology. 3(3), 329-333.

[13]. Polstonm, J. D. & Kentucky, L. (2013). Decentralized Adaptive Control for Uncertain Linear Systems: Technique with Local Full- State Feedback or Local Relative-Degree- One Output Feedback (Master of Science, Mechanical Engineering, College of Engineering, Kentucky University).

[14]. Šiljak, D. D. (1978). Large-Scale Dynamic Systems: Stability and Structure (Vol. 2). North Holland.

[15]. Solheim, O. A. (1972). Design of optimal control systems with prescribed eigenvalues. International Journal of Control, 15(1), 143-160.

[16]. Sombría, J. C., Moreno, J. S., Visioli, A., & Bencomo, S. D. (2012). Decentralised control of a quadruple tank plant with a decoupled event-based strategy. IFAC Proceedings Volumes, 45(3), 424-429.

[17]. Stefanescu, R. M., Prioroc, C. L., & Stoica, A. M. (2013). Weighting Matrices Determination Using Pole Placement For Tracking Maneuvers. UPB Sci. Bull., Series D, 75(2), 31-41.

[18]. Williams, R. L. & Lawrence, D. A. (2007). Linear State- Space Control Systems. John Wiley & Sons.

[19]. Zhang, Y., Wang, Q. G., & Astrom, K. J. (2002). Dominant pole placement for multi-loop control systems. Automatica, 38(7), 1213-1220.

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Research Paper

Optimal Sizing Of Distributed Generations Using Heuristic Optimization Techniques

Mahmoud Abdallah Attia* , Marwa F. Fathi, Ibrahim M. Diaa*

* Department of Electrical Power & Machines, Faculty of Engineering, Ain Shams University, Cairo, Egypt.

Electrical Engineer, Sakr Factory (Arab Organization for Industrialization), Cairo, Egypt.

* Department of Engineering Physics and Mathematics, Faculty of Engineering, Ain Shams University, Cairo, Egypt.

Attia, M.A., Fathi, M.F., and Diaa, I.M. (2017). Optimal Sizing of Distributed Generations using Heuristic Optimization Techniques. i-manager’s Journal on Instrumentation and Control Engineering, 5(3), 10-24. https://doi.org/10.26634/jic.5.3.13678

Abstract

Nowadays Power system suffers from a lot of power flow problems. The main common problems are high power loss and overload of lines. The Distributed Generators (DGs) are considered as one of the efficient solutions for these problems. The DG can generate power at the location of load which helps in power loss problem. Also generation at load location will decrease the power flow in lines. This paper studies the DG sizing by new optimization techniques. Several cases studied in this work to select the suitable techno-economic strategy of DG sizing. Ranges of DG sizing in cases were studied are 40%, 60%, 80% and 100% of system loading. Studies consider trying to improve the voltage profile to certain limits by using the DGs. Finally, suggestion is concluded to which range of sizing is suitable and if the voltage limits consideration is economical or not in DG sizing.

References

[1]. Abd, M. K., Cheng, S. J., & Sun, H. S. (2016, June). Optimal DG placement and sizing for power loss reduction in a radial distribution system using MPGSA and sensitivity index method. In Industrial Electronics and Applications (ICIEA), 2016 IEEE 11 Conference on (pp. 1579-1585). IEEE.

[2]. Ackermann, T., Andersson, G., & Söder, L. (2001). Distributed generation: A definition. Electric Power Systems Research, 57(3), 195-204.

[3]. Baran, M. E., & Wu, F. F. (1989). Network reconfiguration in distribution systems for loss reduction and load balancing. IEEE Transactions on Power Delivery, 4(2), 1401- 1407.

[4]. CIGRÉ Working Group. (1999). Impact of Increasing Contribution of Dispersed Generation on the Power System. CIGRÉ Final Rep, 137.

[5]. Diaa, I. M., Badra, N. M., & Attia, M. A. (2016). Harmony Search and Nonlinear Programming Based Hybrid Approach to Enhance Power System Performance with Wind Penetration. International Electrical Engineering Journal, 7(7), 2323-2330.

[6]. El-Zonkoly, A. M. (2013). Multistage expansion planning for distribution networks including unit commitment. IET Generation, Transmission & Distribution, 7(7), 766-778.

[7]. Falaghi, H., Singh, C., Haghifam, M. R., & Ramezani, M. (2011). DG integrated multistage distribution system expansion planning. International Journal of Electrical Power & Energy Systems, 33(8), 1489-1497.

[8]. Gan, C. K., Mancarella, P., Pudjianto, D., & Strbac, G. (2011). Statistical appraisal of economic design strategies of LV distribution networks. Electric Power Systems Research, 81(7), 1363-1372.

[9]. Garva, N., & Sanghi, A. (2016). Estimation of Optimal Location and Sizing of DG for Minimization of Loss in Radial Distribution System using Meta-Heuristic Technique. International Conference on Emerging Trends in Engineering and Management Sustainable Development.

[10]. Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A New Heuristic Optimization Algorithm: Harmony Search. Simulation, 76(2), 60-68.

[11]. Krueasuk, W., & Ongsakul, W. (2006, December). Optimal placement of distributed generation using Particle Swarm Optimization. In Proceedings of Power Engineering Conference in Australasian Universities, Australia.

[12]. Lotero, R. C., & Contreras, J. (2011). Distribution system planning with reliability. IEEE Transactions on Power Delivery, 26(4), 2552-2562.

[13]. Moreira, J. C., Miguez, E., Vilacha, C., & Otero, A. F. (2011). Large-scale network layout optimization for radial distribution networks by parallel computing. IEEE Transactions on Power Delivery, 26(3), 1946-1951.

[14]. Nadhir, K., Chabane, D., & Tarek, B. (2013). Distributed Generation location and size determination to reduce power losses of a distribution feeder by Firefly Algorithm. International Journal of Advanced Science and Technology, 56, 61-72.

[15]. Prabha, D. R., & Jayabarathi, T. (2014). Determining the optimal location and sizing of distributed generation unit using Plant Growth Simulation Algorithm in a radial distribution network. WSEAS Trans. Syst., 13, 543-550.

[16]. Rao, R. V., Savsani, V. J., & Vakharia, D. P. (2011). Teaching–learning-based optimization: A novel method for constrained mechanical design optimization problems. Computer-Aided Design, 43(3), 303-315.

[17]. Rupa, J. M., & Ganesh, S. (2014). Power flow analysis for radial distribution system using backward/forward sweep method. International Journal of Electrical, Computer, Electronics and Communication Engineering, 8(10), 1540-1544.

[18]. Samper, M. E., & Vargas, A. (2013a). Investment decisions in distribution networks under uncertainty with distributed generation-Part I: Model formulation. IEEE Transactions on Power Systems, 28(3), 2331-2340.

[19]. Samper, M. E., & Vargas, A. (2013b). Investment decisions in distribution networks under uncertainty with distributed generation-Part II: Implementation and results. IEEE Transactions on Power Systems, 28(3), 2341-2351.

[20]. Uniyal, A., & Kumar, A. (2016, March). Comparison of optimal DG placement using CSA, GSA, PSO and GA for minimum real power loss in radial distribution system. In th Power Systems (ICPS), 2016 IEEE 6 International Conference on (pp. 1-6). IEEE.

[21]. Viral, R., & Khatod, D. K. (2012). Optimal planning of distributed generation systems in distribution system: A review. Renewable and Sustainable Energy Reviews, 16(7), 5146-5165.

[22]. Wang, D. T. C., Ochoa, L. F., & Harrison, G. P. (2011). Modified GA and data envelopment analysis for multistage distribution network expansion planning under uncertainty. IEEE Transactions on Power Systems, 26(2), 897-904.

[23]. Zahedi, A. (2011). A review of drivers, benefits, and challenges in integrating renewable energy sources into electricity grid. Renewable and Sustainable Energy Reviews, 15(9), 4775-4779.

[24]. Ziari, I., Ledwich, G., Ghosh, A., & Platt, G. (2013). Optimal distribution network reinforcement considering load growth, line loss, and reliability. IEEE Transactions on Power Systems, 28(2), 587-597.

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Research Paper

Analysis of Acoustic Energy Harvesting

Nitin Sharma* , Shivang Jitendra Khare, Santosh Kumar*

- Undergraduate Scholar, Department of Electrical and Electronics & Communication Engineering, DIT University, Uttarakhand, India.

Assistant Professor, Department of Electrical and Electronics & Communication Engineering, DIT University, Uttarakhand, India.

Sharma, N., Khare, S.J., and Kumar, S. (2017). Analysis of Acoustic Energy Harvesting. i-manager’s Journal on Instrumentation and Control Engineering, 5(3), 25-31. https://doi.org/10.26634/jic.5.3.13679

Abstract

In the present era, there is huge scarcity of energy and to carry out the daily activities, electricity is the major requirement. There is a need to produce electricity at a faster rate. In the basic applications, sound is converted into electrical signals to travel over the media for communication purposes. The application of sound energy as electrical energy can be much beneficial. It can be used to lighten the street lights by using the noise made by vehicles. This technology can also be used in industries, airports, runways. Conversion of sound energy into electrical energy appears to be one of the promising techniques to increase the production of energy without depleting natural resources. The objective of this work is to create a device that can convert the sound energy into electrical energy and harvest it for future need. Huge amount of noise is created in the surrounding by different means and this noise energy is generally let into the atmosphere which is not utilized and goes wasted. This work also describes the use of this conversion method in the surrounding to harvest energy from the vehicular noise, noise created by humans and industrial noise. By doing so, there is a reduction in pollution as well as the efficiency of the machines is increased. In today's world, a suitable method of power generation is required which could benefit the society. Thus, the concept of conversion of sound energy into electrical energy have been well discussed. Various applications based on the conversion have also been highlighted.

References

[1]. Bhatnagar S. R. (2012). Converting sound energy to electric energy. International Journal of Emerging Technology and Advanced Engineering, 2(10), 267-270.

[2]. Chang, J., Dommer, M., Chang, C., & Lin, L. (2012). Piezoelectric nanofibers for energy scavenging applications. Nano Energy, 1(3), 356-371.

[3]. Engel, T. G., Keawboonchuay, C., & Nunnally, W. C. (2000). Energy conversion and high power pulse production using miniature piezoelectric compressors. IEEE Transactions on Plasma Science, 28(5), 1338-1341.

[4]. Gupta, A., Goel, V., & Yadav, V. (2014). Conversion of Sound to Electric Energy. International Journal of Scientific & Engineering Research, 5(1), 2146.

[5]. Jaffe, B., Cook, W. R., & Jaffe, H. (1971). Piezoelectric Ceramic. London: Academic Press.

[6]. Lowrie F., Cain M., & Stewart M. (1999). Time dependent behavior of piezoelectric materials. National Physical Laboratory Management Ltd., Teddington, Middlesex, U. K., NPL Rep. SMMT (A) 151.

[7]. Mukti, N. G., & Yadav, S. K. (2013). Electricity generation due to vibration of moving vehicles using piezoelectric effect. Research India Publication, 4(3), 313-318.

[8]. Padhi, K. S., & Prabhu, S. Application of Nano generators-PZT to Operate Nanodevices: A Noise Energy Survey Analysis Approach. IOSR Journal of Electrical and Electronics Engineering, 9(1), 1-9.

[9]. Park, J. C., Kim, Y. S., & Kang, D. J. (2008). Propagation Characteristics and Effects of Road Traffic Noise. Korean Journal of Environmental Health Sciences, 34(4), 311-315.

[10]. Priya, S., & Myers, R. D. (2010). Piezoelectric Energy Harvester. U.S. Patent No. 7,649,305. Washington, DC: U.S. Patent and Trademark Office.

[11]. Revathi, G., & Ingitham, R. (2012). Piezoelectric Energy Harvesting System in Mobiles with Keypad and Sound Vibrations. International Journal of Engineering Research & Technology (IJERT), 1(4), 1-4.

[12]. Shrivastava S., Gome M., Purohit S., Mundra C., & Pawar S. S. (2014). Converting sound energy into electricity using piezoelectric material: A Study. International Journal of Mechanical Engineering & Technology, 5(1), 116-121.

[13]. Tomar P., Kumar P., Ali, N., Kumar, S., Musharraf, T. & Kumar, P. (2016). Conversion of Noise Pollution to Electrical Energy. International Journal of Advanced Research in Science and Engineering, 5(3), 514-522.

[14]. Waghulde, K. B., & Kumar, B. (2012). Vibration analysis and control of piezoelectric smart structures by feedback controller along with spectra pulse software. International Journal of Mechanical Engineering & Technology, 3(2), 783-795.

[15]. Yang, G., Liu, S. F., Ren, W., & Mukherjee B.K. (2012). Uniaxial stress dependence of piezoelectric properties of lead zirconatetitanate ceramics. Active Materials: Behavior and Mechanics. Bellingham, WA: SPIE 2000, 3992, 103-113.

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Research Paper

Implementation of Speed Violation and Insurance Detection System Using RFID and Internet of Things

V. Nagendra* , G. Rakshitha, K.T. Siddharth Nambiar, Vyshnavi Lakshmi Burle, Manu D. K.

- Department of Electronics Communication Engineering, KSSEM, Bengaluru, Karnataka, India.

Associate Professor, Department of Electronics Communication Engineering, KSSEM, Bengaluru, Karnataka, India.

Nagendra, V., Rakshitha, G., Nambiar, K.T.S., Burle, V.L., and Manu, D.K. (2017). Implementation of Speed Violation and Insurance Detection System Using RFID and Internet of Things. i-manager’s Journal on Instrumentation and Control Engineering, 5(3), 32-37. https://doi.org/10.26634/jic.5.3.13680

Abstract

Road accidents are a major problem in today's world. The aim of this research is to provide a solution to prevent such accidents. This project is mainly focused on automatically controlling the speed of the vehicles in speed restricted zones, such as schools, hospitals, and speed limit zones. Currently, the system used for monitoring and controlling speed of vehicles in speed-limited zones is ineffective or non-existent. This work proposes a system for controlling the speed of the vehicles within certain limits in restricted zones without driver intervention, and also checks whether a particular vehicle owner has paid insurance or not. Then it provides an alerts to the owner and the traffic control room in case the payment is not done. In this work, an RF transceiver system is used to indicate the speed limited zones, and upon entering such zones, the speed control system installed in the vehicle automatically adjusts the speed accordingly. The same transceivers also monitor the insurance status of the vehicle, and send relevant messages to the owner of the vehicle.

References

[1]. Bhatt, P.P., Chaudhari, K. A., Chaudhary, K. A., Goyal, S. S., & Pandey, A. B. (2014 January). Programming for Automatic over speed Control System for Safety in Automobiles. International Journal on Theoretical and Applied Research in Mechanical Engineering (IJTARME), 3(1), 56-61.

[2]. Bothe, S. S, Jadhav, S. S., Sonawane, P. S., & Bhamare, N.V., (2016). RF based wireless notice board. IOSR Journal of Computer Engineering, 15-17.

[3]. ElShafee, A., & Hamed, K. A. (2012). Design and implementation of a WIFI based home automation system. World Academy of Science, Engineering and Technology, 68, 2177-2180.

[4]. Fan, Y. J., Yin, Y. H., Da Xu, L., Zeng, Y., & Wu, F. (2014). IoT-based smart rehabilitation system. IEEE Transactions on Industrial Informatics, 10(2), 1568-1577.

[5]. https://www.arduino.cc/

[6]. Huang, J., Duan, Q., Zhao, Y., Zheng, Z., & Wang, W. (2017). Multicast Routing for Multimedia Communications in the Internet of Things. IEEE Internet of Things Journal, 4(1), 215-224.

[7]. Kaphungkui, N. K. (2015). RF based Remote Control for Home Electrica appliances. International Journal of Innovative Research In Electrical, Electronics, Instrumentation and Control Engineering, 3(7), 42-44.

[8]. Khan, A., & Mishra, R. (2012). GPS–GSM based tracking system. International Journal of Engineering Trends and Technology, 3(2), 161-164.

[9]. Kodavati, B., Raju, V. K., Rao, S. S., Prabu, A. V., Rao, T. A., & Narayana, D. Y. (2011). GSM and GPS based vehicle location and tracking system. International Journal of Engineering Research and Applications (IJERA), 1(3), 616- 625.

[10]. Laghari, A. A., Memon, M. S., & Pathan, A. S. (2012). RFID based toll deduction system. International Journal of Information Technology and Computer Science (IJITCS), 4(4), 40-46.

[11]. Mishra, Y., Marwah, G. K., & Verma, S. (2015). Arduino based Smart RFID Security and Attendance System with Audio Acknowledgement. International Journal of Engineering Research and Technology, 4(1), 363-367.

[12]. Ngu, A. H., Gutierrez, M., Metsis, V., Nepal, S., &Sheng, Q. Z. (2017). IoT middleware: A survey on issues and enabling technologies. IEEE Internet of Things Journal, 4(1), 1-20.

[13]. Nichat, A. N., Ali, S. K., Solanke, Y. D., & Dodke, A. M. (2015). Wireless Speed and Direction Control of DC Motor by using Radio Frequency Technology. International Journal of Engineering Trends and Technology (IJETT), 20(2), 48-51.

[14]. Majrouhi Sardroud, M. J., & Limbachiya, M. C. (2010). Effective information delivery at construction phase with integrated application of RFID, GPS and GSM technology. In Proceedings of the World Congress on Engineering (Vol. 1).

[15]. Sirisha, K., & Reddy, K. N. (2015). Detection of Vehicle Location and its Emissions using RFID Technology on Internet of Things. International Journal of Eminent Engineering Technologies, 2(5), 96-100.

[16]. Vijaykiran. G, Saikrishna. M,.(2017). IoT based Home Electrical Appliances Control using Node MCU. International Journal of Scientific Engineering and Technology Research, 6(4).

[17]. Wang, C., Daneshmand, M., Dohler, M., Mao, X., Hu, R. Q., & Wang, H. (2013). Guest Editorial-Special issue on internet of things (IoT): Architecture, protocols and services. IEEE Sensors Journal, 13(10), 3505-3510.

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Research Paper

Load Frequency Control of a Thermal Power System using ANFIS and Comparison with Different Controllers

G. Gayathri Devi* , M. Sai Veerraju**

* PG Scholar, Department of Electrical and Electronics Engineering, S.R.K.R Engineering College, Andhra Pradesh, India.

** Professor, Department of Electrical and Electronics Engineering, S.R.K.R Engineering College, Andhra Pradesh, India.

Devi, G.G.,and Veerraju, M.S. (2017). Load Frequency Control of a Thermal Power System using ANFIS and Comparison with Different Controllers. i-manager’s Journal on Instrumentation and Control Engineering, 5(3), 38-46. https://doi.org/10.26634/jic.5.3.13681

Abstract

This paper investigated Load Frequency Control (LFC) using an Artificial Intelligence (AI) technique called Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS controller is simple to apply and at the same time it can handle system nonlinearities very effectively. ANFIS controller gives better dynamic response and it is faster than proposed controllers. Dynamic analysis was done without controller, with Proportional Integral Derivative controller (PID controller), Fuzzy controller, Linear Quadratic Regulator (LQR), and with Adaptive Neuro-Fuzzy Inference System (ANFIS) controller using Matlab/Simulink. The results of ANFIS controller was compared with results obtained from other controllers and it is observed that it has improved system performance in terms of steady state response and reduced oscillations and at the same time it is faster than above proposed controllers.

References

[1]. Çalik, H. & Kakilli, A. (2009). The modelling of electric power systems on the state space and controlling of Optimal LQR Load Frequency. IU-Journal of Electrical & Electronics Engineering, 9(2), 977-982.

[2]. Elgerd, O. I., & Fosha, C. E. (1970). Optimum megawatt-frequency control of multiarea electric energy systems. IEEE Transactions on Power Apparatus and Systems, 4, 556-563.

[3]. Feliachi, A. (1987). Optimal decentralized load frequency control. IEEE Transactions on Power Systems, 2(2), 379-385.

[4]. Fosha, C. E., & Elgerd, O. I. (1970). The megawattfrequency control problem: A new approach via Optimal Control Theory. IEEE Transactions on Power Apparatus and Systems, 4, 563-577.

[5]. Gross, G., & Lee, J. W. (2001). Analysis of load frequency control performance assessment criteria. IEEE Transactions on Power Systems, 16(3), 520-525.

[6]. Hamza, M. H., Agathoklis, P., & Chan, W. C. (1982). A combined self-tuning and integral controller for load frequency control of interconnected power systems. Automatisierungstechnik, 30(1-12), 226-232.

[7]. Ikhe, A., & Kulkarni, A. (2013). Load Frequency Control for Two Area Power System using different Controllers. International Journal of Advances in Engineering & Technology, 6(4), 1796-1802.

[8]. Kothari, D. P., Nagarath, I. J., (2003). Modern Power rd System Analysis,3 Ed. Tata McGro Hill.

[9]. Kumar, P., & Kothari, D. P. (2005). Recent philosophies of automatic generation control strategies in power systems. IEEE Transactions on Power Systems, 20(1), 346-357.

[10]. Kundur, P., (1994). Power System Stability and Control. Mc Graw hill New York.

[11]. Lee, C. C., (1990). Fuzzy logic in control systems: Fuzzy logic controller- part 2. IEEE Trans. Syst. Man Cybern., 20(2), 419-35.

[12]. Masiala, M., Ghribi, M., & Kaddouri, A. (2004, December). An adaptive fuzzy controller gain scheduling for power system load-frequency control. In Industrial Technology, 2004. IEEE ICIT'04. 2004 IEEE International Conference on (Vol. 3, pp. 1515-1520). IEEE.

[13]. Mendel, J. M., (1995, March). Fuzzy Logic Systems for engineering: A Tutorial. Proceeding of the IEEE, 83(3), 345- 377.

[14]. Parmar, K. S., Majhi, S., & Kothari, D. P. (2010, December). Multi-area load frequency control in a power system using optimal output feedback method. In Powern Electronics, Drives and Energy Systems (PEDES) & 2010 Power India, 2010 Joint International Conference on (pp. 1-5). IEEE.

[15]. Prakash, S., Bhardwaj, A. K., & Sinha, S. K. (2012, December). Neuro fuzzy hybrid intelligent approach for four-area load frequency control of interconnected power system. In Power, Control and Embedded Systems nd (ICPCES), 2012 2 International Conference on (pp. 1-7). IEEE.

[16]. Rao, C. S. (2012, March). Adaptive Neuro Fuzzy based Load Frequency Control of multi area system under open market scenario. In Advances in Engineering, Science and Management (ICAESM), 2012 International Conference on (pp. 5-10). IEEE.

[17]. Ross, T. J. (2009). Fuzzy Logic with Engineering Applications. John Wiley & Sons.

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Research Paper

Optimal State Feedback Controller for Coordinated Control of Series Vectorial Compensator and Power System Stabilizer

K. Himaja * , T.S. Surendra, S. Tara Kalyani*

* Lecturer, Department of Technical Education, Government of Andhra Pradesh, India.

Director, Department of Energy Systems, Visionary Lighting and Energy, Hyderabad, India.

* Professor & Head, Department of Electrical and Electronics Engineering, JNTUH, Hyderabad, India.

Himaja, K., Surendra, T.S., and Kalyani, S.T. (2017). Optimal State Feedback Controller for Coordinated Control of Series Vectorial Compensator and Power System Stabilizer. i-manager’s Journal on Instrumentation and Control Engineering, 5(3), 47-58. https://doi.org/10.26634/jic.5.3.13682

Abstract

This paper presents a comprehensive approach for Coordinated Control (COC) of Series Vectorial Compensator (SVeC) and Power System Stabilizer (PSS) for damping Low Frequency Oscillations (LFO) in multimachine networks. SVeC is viewed as the most innovational series Flexible AC Transmission System (FACTS) device. Though PSS and SVeC devices have been incorporated separately in multi machine networks, optimal control strategy based on state feedback control for coordination of PSS and SVeC controllers under different loading conditions has not been developed. So, the Optimal State Feedback Controller (OSFC) for incorporating of PSS and SVeC controllers in COC manner has been developed in this paper. The performance of the aforesaid method is checked using eigen-value analysis and nonlinear time- domain simulation outcomes under numerous loading conditions together with nominal case. The comparison of performance of COC of SVeC and PSS in a Western System Coordinating Council (W.S.C.C) 3-machine, 9-bus system is investigated in this paper. The damping characteristics of the optimal controller for COC of SVeC and PSS are compared with COC, PSS and without control are analyzed. The outcomes of test system show that the proposed optimal control can improve the dynamic stability of test system significantly at different loading conditions.

References

[1]. Aldeen, M., & Crusca, F. (1995). Multimachine power system stabiliser design based on new LQR approach. IEE Proceedings-Generation, Transmission and Distribution, 142(5), 494-502.

[2]. Ba-muqabel, A. A., & Abido, M. A. (2006, March). Review of conventional power system stabilizer design methods. In GCC Conference (GCC), 2006 IEEE (pp. 1-7). IEEE.

[3]. Canizares, C. A., & Faur, Z. T. (1999). Analysis of SVC and TCSC controllers in voltage collapse. IEEE Transactions on Power Systems, 14(1), 158-165.

[4]. Gonzalez, J. M., Canizares, C. A., & Ramirez, J. M. (2010). Stability modeling and comparative study of series vectorial compensators. IEEE Transactions on Power Delivery, 25(2), 1093-1103.

[5]. Himaja, K., Surendra. T. S., & Kalyani. S. T. (2016). Coordinated design of PSS and Series Vectorial Compensator controllers for damping power system oscillations. Journal of Electrical Engineering, 16(4), 500- 507.

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i-manager's Journal on Instrumentation and Control Engineering (JIC)

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Volume 5 Issue 3 May - July 2017

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Optimal Sizing Of Distributed Generations Using Heuristic Optimization Techniques

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Analysis of Acoustic Energy Harvesting

Nitin Sharma* , Shivang Jitendra Khare**, Santosh Kumar***

*-** Undergraduate Scholar, Department of Electrical and Electronics & Communication Engineering, DIT University, Uttarakhand, India. *** Assistant Professor, Department of Electrical and Electronics & Communication Engineering, DIT University, Uttarakhand, India.

Sharma, N., Khare, S.J., and Kumar, S. (2017). Analysis of Acoustic Energy Harvesting. i-manager’s Journal on Instrumentation and Control Engineering, 5(3), 25-31. https://doi.org/10.26634/jic.5.3.13679

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Implementation of Speed Violation and Insurance Detection System Using RFID and Internet of Things

V. Nagendra* , G. Rakshitha**, K.T. Siddharth Nambiar***, Vyshnavi Lakshmi Burle****, Manu D. K.*****

*-**** Department of Electronics Communication Engineering, KSSEM, Bengaluru, Karnataka, India. ***** Associate Professor, Department of Electronics Communication Engineering, KSSEM, Bengaluru, Karnataka, India.

Nagendra, V., Rakshitha, G., Nambiar, K.T.S., Burle, V.L., and Manu, D.K. (2017). Implementation of Speed Violation and Insurance Detection System Using RFID and Internet of Things. i-manager’s Journal on Instrumentation and Control Engineering, 5(3), 32-37. https://doi.org/10.26634/jic.5.3.13680

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Load Frequency Control of a Thermal Power System using ANFIS and Comparison with Different Controllers

G. Gayathri Devi* , M. Sai Veerraju**

* PG Scholar, Department of Electrical and Electronics Engineering, S.R.K.R Engineering College, Andhra Pradesh, India. ** Professor, Department of Electrical and Electronics Engineering, S.R.K.R Engineering College, Andhra Pradesh, India.

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Optimal State Feedback Controller for Coordinated Control of Series Vectorial Compensator and Power System Stabilizer

K. Himaja * , T.S. Surendra**, S. Tara Kalyani***

* Lecturer, Department of Technical Education, Government of Andhra Pradesh, India. ** Director, Department of Energy Systems, Visionary Lighting and Energy, Hyderabad, India. *** Professor & Head, Department of Electrical and Electronics Engineering, JNTUH, Hyderabad, India.

Himaja, K., Surendra, T.S., and Kalyani, S.T. (2017). Optimal State Feedback Controller for Coordinated Control of Series Vectorial Compensator and Power System Stabilizer. i-manager’s Journal on Instrumentation and Control Engineering, 5(3), 47-58. https://doi.org/10.26634/jic.5.3.13682

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* Lecturer, Department of Communications and Electronics Engineering., College of Engineering, Umm Al-Qura University, Al-Lith Branch, KSA.

** Professor, Department of Electrical Engineering, Faculty of Engineering, Minia University, Egypt.

Mahmoud Abdallah Attia* , Marwa F. Fathi, Ibrahim M. Diaa*

Nitin Sharma* , Shivang Jitendra Khare, Santosh Kumar*

- Undergraduate Scholar, Department of Electrical and Electronics & Communication Engineering, DIT University, Uttarakhand, India.

Assistant Professor, Department of Electrical and Electronics & Communication Engineering, DIT University, Uttarakhand, India.

V. Nagendra* , G. Rakshitha, K.T. Siddharth Nambiar, Vyshnavi Lakshmi Burle, Manu D. K.

- Department of Electronics Communication Engineering, KSSEM, Bengaluru, Karnataka, India.

Associate Professor, Department of Electronics Communication Engineering, KSSEM, Bengaluru, Karnataka, India.

* PG Scholar, Department of Electrical and Electronics Engineering, S.R.K.R Engineering College, Andhra Pradesh, India.

** Professor, Department of Electrical and Electronics Engineering, S.R.K.R Engineering College, Andhra Pradesh, India.

K. Himaja * , T.S. Surendra, S. Tara Kalyani*

* Lecturer, Department of Technical Education, Government of Andhra Pradesh, India.

Director, Department of Energy Systems, Visionary Lighting and Energy, Hyderabad, India.

* Professor & Head, Department of Electrical and Electronics Engineering, JNTUH, Hyderabad, India.