Comparative Performance Analysis of PID, Fuzzy-Mamdani, Fuzzy-Sugeno and ANFIS for Automatic Generation Control of Multi-Area Power System

Umesh Kumar Singh*, L. B. Prasad**
* PG Scholar, Department of Electrical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, India.
** Assistant Professor, Department of Electrical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, India.
Periodicity:July - September'2016
DOI : https://doi.org/10.26634/jee.10.1.8199

Abstract

Automatic Generation Control (AGC) insures a sufficient, reliable and good quality of power to the consumer. It insures that the amount of power available should be sufficient and the frequency deviation is within the rated limit. Any mismatch between generation and demand causes deviation in the system frequency from its nominal value. If load is continuously changing in nature, the frequency deviation goes on increasing, which may lead to system collapse. So in order to maintain the stability in power generation, a very fast and accurate controller is needed to maintain the nominal system frequency. In this paper, Proportional- Integral-Derivative controller and artificial intelligent controllers such as Fuzzy-Mamdani, Fuzzy-Sugeno and Adaptive Neuro Fuzzy Inference System (ANFIS) has been presented for AGC of fourarea (Thermal-Nuclear-Thermal-Hydro) interconnected power system including Generation Rate Constraint (GRC).

Keywords

Automatic Generation Control (AGC), Adaptive Neuro Fuzzy Inference System (ANFIS), Generation Rate Constraint (GRC), Fuzzy Logic Controller (FLC)

How to Cite this Article?

Singh, U.K., and Prasad, L. B. (2016). Comparative Performance Analysis of PID, Fuzzy-Mamdani, Fuzzy-Sugeno and ANFIS for Automatic Generation Control of Multi-Area Power System. i-manager’s Journal on Electrical Engineering, 10(1), 26-34. https://doi.org/10.26634/jee.10.1.8199

References

[1]. Gayadhar Panda, Sidharth Panda and Cemal Ardil, (2009). “Automatic generation control of interconnected power system with GRC byhybrid neuro-fuzzy approach”. World Academy of Science Engineering and Technology, Vol. 6, No.4, pp. 543-548.
[2]. Mavungu Masiala, Mohsen Ghribi and Azeddine Kaddouri, (2012). “A Two-Layered Load and Frequency Controller of a Power System, Fuzzy Controllers”. Recent Advances in Theory and Applications, pp. 503-518.
[3]. O.I. Elgerd, C.E. Fosha, (1970). “Optimum megawatt frequency control of multi-area electric energy systems”. IEEE Transation on PAS, Vol. PAS-89, No.4, pp. 556-563.
[4]. J. Nanda, B. Kaul, (1978). “Automatic generation control of an interconnected power system”. IEEE Proceedings, pp. 385-390.
[5]. J.R. Jung, (1993). “ANFIS, Adaptive Network based Fuzzy Inference System”. IEEE Transation on System, Man and Cybernetics, Vol. 23, No. 3, pp. 665-685.
[6]. Swasti R. Khuntia, and Sidhartha Panda, (2011). “A Novel approach for automatic generation control of multi-area power system”. IEEE Conference on Electrical and Computer Engineering, pp. 1182-1187.
[7]. D.P. Kothari, and I.J. Nagrath, (2009). Modern Power System Analysis. Third Edition 2009.
[8]. A. Demiroren, and E. Yesil, (2004). “Automatic generation control with fuzzy logic controllers in power system including SMES unit”. International Journal of Electrical Power and Energy Systems, pp. 291-305.
[9]. Surya Praksah and Sunil Kumar Sinha, (2015). “Performance evalution of hybrid intelligent controllers in load frequency of multi-area interconnected power system”. World Academy of Science, Engineering and Technology, pp. 637-645.
[10]. T. Ichikawa, (1976). Dynamics of Nuclear Power Plant in Electric Power System (Part 1)-BWR Plant. CRIEPI Report No. 175079.
[11]. Sanjoy Debbarma, and Lalit Chandra Saikia, (2012). “Automatic generation control of multi-area system using non-integer I?Dµ controller”. IEEE Transaction on Power and Engineering in NERIST, pp. 1-6
[12]. Kaveh Rahimi and Parviz Famouri, (2013). “Performance enhancement of automatic generation control for a multi-area power system in the presence of communication delay ”. North American Power Symposium, pp. 1-6.
[13]. II Kim, Jae-Hyun Lee, and Eun-oh Bang, (1999). “A new approach to adaptive membership function for fuzzy inference system”. IEEE Conference on Knowledge Based Intelligent Information System, pp. 112-116.
[14]. Otman, M. Ahtiwash, Mohz. Z. Abdulmuin and Fatimah Siraj, (2002). “A neural-fuzzy logic approach for modelling and control of non-linear system”. IEEE International Symposium on Intelligent Control, pp. 270-275.
[15]. B.H. Simon, R. Raghavan, and T. Tochigi, (1993). “Control of multiple nuclear power plant from a single detached and control facility”. IEEE Conference on Nuclear Science Symposium, pp. 941-945.
[16]. M. Parida, and J. Nanda, (2005). “Automatic generation control of a hydro-thermal sysem in deregulated environment”. IEEE Proceedings on Electrical Machines and Systems, pp. 942-947.
[17]. L.J Puthmana, and J. Abdul Jaleel, (2011). “Performance evalution of AGC of SHP multi-area power system”. IEEE Conference on Power and Energy System, pp. 01-05.
[18]. K.V. Siva Reddy, (2013). “An adaptive neuro-fuzzy logic controller for a two area load frequency control”. International Journal of Engineering Research and Application, pp. 989-995.
[19]. C. Srinivasa Rao, (2012). “Aadptive neuro fuzzy based load frequency control of multi-area system under open market scenario”. IEEE Conference on Advances in Engineering Science and Management, pp. 05-10.
[20]. A. Alwadie, (2012). “Stablizing load frequency of a single area power system with uncertain parameters through a genetically tuned PID controller”. International Journal of Engineering and Computer Science, pp. 51- 57.
[21]. Javad Javidan, and Ali Ghasemi, (2013). “A novel fuzzy RPID controller for multi-area automatic generation control with IABC optimization”. Hindawi Publishing Corporation Journal of Engineering, pp. 01-13.
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