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Research Article |

A New Soft Computing Fuzzy Logic Frequency Regulation Scheme for Two Area Hybrid Power Systems

Author(s): Namburi Nireekshana*, R. Ramachandran and G. V. Narayana

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 11, Issue 3

Publisher : FOREX Publication

Published : 10 August 2023

e-ISSN : 2347-470X

Page(s) : 705-710

DOI: https://doi.org/10.37391/ijeer.110310

Abstract

Modern renewable energy power system designs provide significant application benefits, but they also produce losses. The total generation, total load demand, and system losses must be balanced in order for this structured power system to operate reliably. The actual and reactive power balances are disturbed as a result of changes in load demand. System frequency and tie line interchange power deviate from their planned values as a result of this. A high system frequency deviation can cause the system to crash. In that case, multiple connect area systems use intelligent load frequency control techniques to deliver dependable and high-quality frequency and tie line power flow. Here, a standalone hybrid power system is taken into consideration, with generated power and frequency being controlled intelligently. In addition to the unpredictable nature of the wind, frequent adjustments in the load profile can produce sizeable and detrimental power variations. The output power of such renewable sources may fluctuate to the point that it causes significant frequency and voltage changes in the grid. An intelligent approach recently proposed to address the load frequency control (LFC) issue of an interconnected power system is known as fuzzy logic PID controller (FLPIDC). Standard proportional integral derivative (PID) controllers are used to control each section of the system.

Keywords: hybrid power system, Load Frequency Control, FLPIDC, PID..




Namburi Nireekshana*, Department of Electrical Engineering, Faculty of Engineering and Technology, Annamalai University, Tamil Nadu; Email: nireekshan222@gmail.com

R. Ramachandran, Department of Electrical Engineering, Faculty of Engineering and Technology, Annamalai University, Tamil Nadu; Email: ramachandran.auee@gmail.com

G. V. Narayana, Department of Electrical & Electronics Engineering, Faculty of Engineering and Technology, JNTUA, AP; Email: gv1.venkata@gmail.com

    [1] A. Annamraju and S. Nandiraju, “A novel fuzzy tuned multistage PID approach for frequency dynamics control in an islanded microgrid,” Int. Trans. Electr. Energy Syst., vol. 30, no. 12, p. e12674, 2020. [Cross Ref]
    [2] A. Annamraju, L. Bhukya, and S. Nandiraju, “Robust frequency control in a standalone microgrid: An adaptive fuzzy based fractional order cascade PD-PI approach,” Adv. Control Appl. Eng. Ind. Syst., vol. 3, no. 3, p. e72, 2021. [Cross Ref]
    [3] A. Annamraju and S. Nandiraju, “Frequency control in an autonomous two-area hybrid microgrid using grasshopper optimization based robust PID controller,” in 2018 8th IEEE India International Conference on Power Electronics (IICPE), IEEE, 2018, pp. 1–6. [Cross Ref]
    [4] A. Annamraju and S. Nandiraju, “Robust frequency control in a renewable penetrated power system: an adaptive fractional order-fuzzy approach,” Prot. Control Mod. Power Syst., vol. 4, pp. 1–15, 2019. [Cross Ref]
    [5] S. V. Kamble and S. M. Akolkar, “Load frequency control of micro hydro power plant using fuzzy logic controller,” in 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), IEEE, 2017, pp. 1783–1787. [Cross Ref]
    [6] J. Sun, M. Chen, L. Kong, Z. Hu, and V. Veerasamy, “Regional Load Frequency Control of BP-PI Wind Power Generation Based on Particle Swarm Optimization,” Energies, vol. 16, no. 4, p. 2015, 2023. [Cross Ref]
    [7] N. Ram Babu, S. K. Bhagat, L. C. Saikia, T. Chiranjeevi, R. Devarapalli, and F. P. García Márquez, “A comprehensive review of recent strategies on automatic generation control/load frequency control in power systems,” Arch. Comput. Methods Eng., vol. 30, no. 1, pp. 543–572, 2023. [Cross Ref]
    [8] R. El-Sehiemy, A. Shaheen, A. Ginidi, and S. F. Al-Gahtani, “Proportional-Integral-Derivative Controller Based-Artificial Rabbits Algorithm for Load Frequency Control in Multi-Area Power Systems,” Fractal Fract., vol. 7, no. 1, p. 97, 2023. [Cross Ref]
    [9] U. Raj and R. Shankar, “Optimally enhanced fractional-order cascaded integral derivative tilt controller for improved load frequency control incorporating renewable energy sources and electric vehicle,” Soft Comput., pp. 1–21, 2023. [Cross Ref]
    [10] E. Bahrampour, M. Dehghani, M. H. Asemani, and R. Abolpour, “Load frequency fractional-order controller design for shipboard microgrids using direct search alghorithm,” IET Renew. Power Gener., vol. 17, no. 4, pp. 894–906, 2023. [Cross Ref]
    [11] P. R. Sahu et al., “Effective Load Frequency Control of Power System with Two-Degree Freedom Tilt-Integral-Derivative Based on Whale Optimization Algorithm,” Sustainability, vol. 15, no. 2, p. 1515, 2023. [Cross Ref]
    [12] K. Singh and Y. Arya, “Tidal turbine support in microgrid frequency regulation through novel cascade Fuzzy-FOPID droop in de-loaded region,” ISA Trans., vol. 133, pp. 218–232, 2023. [Cross Ref]
    [13] Y. Güler and I. Kaya, “Load Frequency Control of Single-Area Power System with PI–PD Controller Design for Performance Improvement,” J. Electr. Eng. Technol., pp. 1–16, 2023. [Cross Ref]
    [14] M. Vargheese, S. Vanithamani, D. S. David, and G. R. K. Rao, “Design of fuzzy logic control framework for qos routing in manet,” Intell. Autom. Soft Comput., vol. 35, no. 3, pp. 3479–3499, 2023. [Cross Ref]
    [15] P. Chotikunnan, R. Chotikunnan, A. Nirapai, A. Wongkamhang, P. Imura, and M. Sangworasil, “Optimizing Membership Function Tuning for Fuzzy Control of Robotic Manipulators Using PID-Driven Data Techniques,” J. Robot. Control JRC, vol. 4, no. 2, pp. 128–140, 2023. [Cross Ref]
    [16] H. Huang, H. Xu, F. Chen, C. Zhang, and A. Mohammadzadeh, “An Applied Type-3 Fuzzy Logic System: Practical Matlab Simulink and M-Files for Robotic, Control, and Modeling Applications,” Symmetry, vol. 15, no. 2, p. 475, 2023. [Cross Ref]
    [17] A. Mancilla, O. Castillo, and M. G. Valdez, “Optimization of fuzzy logic controllers with distributed bio-inspired algorithms,” Recent Adv. Hybrid Intell. Syst. Based Soft Comput., pp. 1–11, 2021. [Cross Ref]
    [18] M. Zangeneh, E. Aghajari, and M. Forouzanfar, “A review on optimization of fuzzy controller parameters in robotic applications,” IETE J. Res., vol. 68, no. 6, pp. 4150–4159, 2022. [Cross Ref]
    [19] S. Rajasekaran and G. V. Pai, Neural networks, fuzzy systems and evolutionary algorithms: Synthesis and applications. PHI Learning Pvt. Ltd., 2017.
    [20] M. Jain and M. P. Singh, “Neuro-Fuzzy Controller for Two-Group Pattern Classification Problems.,” in Artificial Intelligence and Applications, 2005, pp. 273–278.
    [21] R. Saraswat and S. Suhag, “Type-2 fuzzy logic PID control for efficient power balance in an AC microgrid,” Sustain. Energy Technol. Assess., vol. 56, p. 103048, 2023. [Cross Ref]
    [22] J. Han, X. Shan, H. Liu, J. Xiao, and T. Huang, “Fuzzy gain scheduling PID control of a hybrid robot based on dynamic characteristics,” Mech. Mach. Theory, vol. 184, p. 105283, 2023. [Cross Ref]
    [23] P. Chotikunnan and Y. Pititheeraphab, “Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application,” J. Robot. Control JRC, vol. 4, no. 2, pp. 217–226, 2023. [Cross Ref]
    [24] D. Gadjiev, A. Rustanov, and I. Kochetkov, “The advanced defuzzification methods of the convex α–cut fuzzy sets,” in E3S Web of Conferences, EDP Sciences, 2023. [Cross Ref]
    [25] M. Nachaoui, A. Nachaoui, R. Y. Shikhlinskaya, and A. Elmoufidi, “An improved hybrid defuzzification method for fuzzy controllers,” Stat. Optim. Inf. Comput., vol. 11, no. 1, pp. 29–43, 2023. [Cross Ref]

Namburi Nireekshana, R. Ramachandran and G. V. Narayana (2023), A New Soft Computing Fuzzy Logic Frequency Regulation Scheme for Two Area Hybrid Power Systems. IJEER 11(3), 705-710. DOI: 10.37391/ijeer.110310.