Frequency Deviation Control Incorporating Fuzzy plus Non-Integer PID Controller in EV based Unified System
Abstract
Different secondary controllers are necessary for Frequency deviation control to meet anticipated power generation related to load demand. In this work a Fuzzy plus Non-Integer PID Controller (FNPID) is projected for frequency deviation control in unified system including EV aggregators. EVs are given priority because of its green environmental effect. Proper adjustment of gains of FNPID is also required to extract the best performance of the secondary controllers. Here a recent tuning process named as multi-verse optimizer (MVO) is applied for proper tuning of projected controller. The implemented dual area power system includes time varying delay-based EV aggregators and thermal generating units. The MVO technique is applied in the model to tune the controller constraints with abrupt increment of demand in one of the control areas. A time-based function is treated as fitness function to evaluate the system performance. The dominance property of the projected FNPID controller over conventional PID controller in terms of different response specifications like maximum positive deviation (overshoot), settling time and minimum negative deviation (undershoot). The robust nature of the projected controller is also confirmed by multiple analysis like random load deviations and system constraint alteration.
Keywords
Full Text:
PDFReferences
O.I. Elgerd, Electric Energy Systems Theory. An introduction. New Delhi: Tata McGraw-Hill; 1983.
Jaleeli, Nasser, et al. "Understanding automatic generation control." IEEE transactions on power systems 7.3 (1992): 1106-1122.
Nanda J, Mangla A, Suri S. Some new findings on automatic generation control of an interconnected hydrothermal system with conventional controllers. Energy Conversion, IEEE Trans. 2006; 21:187-194.
Saikia LC, Nanda J, Mishra S. Performance comparison of several classical controllers in AGC for multi-area interconnected thermal system. International Journal of Electrical Power & Energy System 2011; 33:394-401.
Mudi KR, Pal RN.A robust self-tuning scheme for PI-and PD-type fuzzy controllers. IEEE Transactions on fuzzy system 1999; 7:2–16.
Abraham RJ, Das D, Patra A. Automatic generation control of an interconnected hydrothermal power system considering superconducting magnetic energy storage. International Journal of Electrical Power & Energy System 2007; 29:571-579.
Abraham RJ, Das D. Effect of TCPS on oscillations in tie-power and area frequencies in an interconnected hydrothermal power system. IET Generation Transmission and Distr. 2007; 1:632-639.
Golpira H, Bevrani H.Application of GA optimization for automatic generation control design in an interconnected power system. Energy Conversion and Management 2011; 52:2247-2255.
Ghoshal SP.Optimizations of PID gains by particle swarm optimizations in fuzzy based automatic generation control. Electric Power Systems Res. 2004; 72:203-212
Farahani, M., Ganjefar, S., & Alizadeh, M. (2012). PID controller adjustment using chaotic optimisation algorithm for multi-area load frequency control. IET Control Theory & Applications, 6(13), 1984–1992. doi:10.1049/iet-cta.2011.0405
Çam, E., & Kocaarslan, I. (2005). Load frequency control in two area power systems using fuzzy logic controller. Energy Conversion and Management, 46(2), 233–243. doi:10.1016/j.enconman.2004.02.022
Khuntia SR, Panda S.Simulation study for automatic generation control of a multi-area power system by ANFIS approach. Applied soft compt. 2012; 12:333-341.
Arya Y. AGC of restructured multi-area multi-source hydrothermal power systems incorporating energy storage units via optimal fractional-order fuzzy PID controller. Neural Computing and Applications (2017): 1-22.
Debnath, M. K., Mallick, R. K., & Sahu, B. K. (2017).Application of hybrid differential evolution–grey wolf optimization algorithm for automatic generation control of a multi-source interconnected power system using optimal fuzzy–PID controller. Electric Power Components and Systems, 45(19), 2104–2117. doi:10.1080/15325008.2017.1402221
Pan, I., & Das, S. (2015). Fractional order AGC for distributed energy resources using robust optimization. IEEE transactions on smart grid, 7(5), 2175-2186.
Mohanty, P. K., Sahu, B. K., Pati, T. K., Panda, S., & Kar, S. K. (2016). Design and analysis of fuzzy PID controller with derivative filter for AGC in multi-area interconnected power system. IET Generation, Transmission & Distribution, 10(15), 3764-3776.
Morsali, J., Zare, K., & Hagh, M. T. (2018). A novel dynamic model and control approach for SSSC to contribute effectively in AGC of a deregulated power system. International Journal of Electrical Power & Energy Systems, 95, 239-253.
Tasnin, W., & Saikia, L. C. (2018). Performance comparison of several energy storage devices in deregulated AGC of a multi-area system incorporating geothermal power plant. IET Renewable Power Generation, 12(7), 761-772.
Sahu, Prakash Chandra, et al. "Improved-salp swarm optimized type-II fuzzy controller in load frequency control of multi area islanded AC microgrid." Sustainable Energy, Grids and Networks 16 (2018): 380-392.
Patel, Nimai Charan, Binod Kumar Sahu, and Manoj Kumar Debnath. "Automatic generation control analysis of power system with nonlinearities and electric vehicle aggregators with time-varying delay implementing a novel control strategy." Turkish Journal of Electrical Engineering & Computer Sciences 27, no. 4 (2019): 3040-3054.
Mohapatra, Gayatri, Manoj Kumar Debnath, and Krushna Keshab Mohapatra. "IMO- based novel adaptive dual-mode controller design for AGC investigation in different types of systems." Cogent Engineering 7.1 (2020): 1711675.
Bagheri, Amir, Ali Jabbari, and Saleh Mobayen. "An intelligent ABC-based terminal sliding mode controller for load-frequency control of islanded micro-grids." Sustainable Cities and Society 64 (2021): 102544.
Oshnoei, Soroush, Arman Oshnoei, Ali Mosallanejad, and Farhad Haghjoo. "Novel load frequency control scheme for an interconnected two-area power system including wind turbine generation and redox flow battery." International Journal of Electrical Power & Energy Systems 130 (2021): 107033.
Çelik, Emre. "Design of new fractional order PI–fractional order PD cascade controller through dragonfly search algorithm for advanced load frequency control of power systems." Soft Computing 25, no. 2 (2021): 1193-1217.
Guha, Dipayan, Provas K. Roy, and Subrata Banerjee. "Equilibrium optimizer?tuned cascade fractional?order 3DOF?PID controller in load frequency control of power system having renewable energy resource integrated." International Transactions on Electrical Energy Systems 31, no. 1 (2021): e12702.
Jena, Narendra Kumar, et al. "Design of fractional order cascaded controller for AGC of a deregulated power system." Journal of Control, Automation and Electrical Systems 33.5 (2022): 1389-1417.
Mirjalili, Seyedali, Seyed Mohammad Mirjalili, and Abdolreza Hatamlou. "Multi-verse optimizer: a nature-inspired algorithm for global optimization." Neural Computing and Applications 27, no. 2 (2016): 495-513.
Siti, M. W., et al. "Application of load frequency control method to a multi-microgrid with energy storage system." Journal of Energy Storage 52 (2022): 104629.
Ahmed, Mohamed, et al. "Modified TID controller for load frequency control of a two-area interconnected diverse-unit power system." International Journal of Electrical Power & Energy Systems 135 (2022): 107528.
Dutta, Ankush, and Surya Prakash. "Utilizing electric vehicles and renewable energy sources for load frequency control in deregulated power system using emotional controller." IETE Journal of Research 68.2 (2022): 1500-1511.
DOI (PDF): https://doi.org/10.20508/ijrer.v13i2.13934.g8761
Refbacks
- There are currently no refbacks.
Online ISSN: 1309-0127
Publisher: Gazi University
IJRER is cited in SCOPUS, EBSCO, WEB of SCIENCE (Clarivate Analytics);
IJRER has been cited in Emerging Sources Citation Index from 2016 in web of science.
WEB of SCIENCE in 2025;
h=35,
Average citation per item=6.59
Last three Years Impact Factor=(1947+1753+1586)/(146+201+78)=5286/425=12.43
Category Quartile:Q4