Two-area load frequency control with redox ow battery using intelligent algorithms in a restructured scenario

Two-area load frequency control with redox ow battery using intelligent algorithms in a restructured scenario

Load frequency control (LFC) is an essential aspect of power system dynamics. This paper focuses on the optimization of LFC for a two-area deregulated power system under different scenarios. A recent nature-inspired ower pollination algorithm (FPA), based on the pollination process of plants, is used to tune the proportional integral (PI) controller parameters of LFC for the global minima solution. FPA is compared with a genetic algorithm, particle swarm optimization, and a conventional PI controller. During large load disturbance in the areas, controllers are incapable of reducing frequency deviations and tie-line power oscillations due to the slow response of the speed governor mechanism. Hence, to improve the dynamic response of the LFC, redox ow batteries (RFBs) are added to both areas due to their quick response and lower time constant. The simulation results show the effectiveness of the RFBs and FPA, especially in terms of overshoots, undershoots, and settling time, thereby improving the performance of LFC in the deregulated power system. The simulation was carried out on the MATLAB/Simulink platform.

___

  • [1] Elgerd OI. Electric Energy Systems Theory: An Introduction. 2nd ed. New York, NY, USA: McGraw-Hill, 1983.
  • [2] Kumar J, Ng KH, Sheble G. AGC simulator for price-based operation part I. IEEE T Power Syst 1997; 12: 527-532.
  • [3] Christie RD, Bose A. Load frequency control issues in power system operation after deregulation. IEEE T Power Syst 1996; 11: 1191-1200.
  • [4] Aditya SK, Das D. Battery energy storage for load frequency control of an interconnected power system. Electr Pow Syst Res 2001; 58: 179-185.
  • [5] Kumar SR, Ganapathy S. Impact of energy storage units on load frequency control of deregulated power systems. Energy 2016; 97: 214-228.
  • [6] Pappachen A, Fathima AP. Load frequency control in deregulated power system integrated with SMES{TCPS combination using ANFIS controller. Int J Elec Power 2016; 82: 519-534.
  • [7] Sasaki T, Kadoya T, Enomoto K. Study on load frequency control using redox ow batteries. IEEE T Power Syst 2004; 19: 660-667.
  • [8] Chidambaram IA, Paramasivam B. Optimized load-frequency simulation in restructured power system with redox ow batteries and interline power ow controller. Int J Elec Power 2013; 50: 9-24.
  • [9] Donde V, Pai MA, Hiskens IA. Simulation and optimization in an AGC system after deregulation. IEEE T Power Syst 2001; 16: 481-489.
  • [10] Shayeghi H, Shayanfar HA, Jalili A. Load frequency control strategies: a state-of-the-art survey for the researcher. Energ Convers Manage 2009; 50: 344-353.
  • [11] Tyagi B, Srivastava SC. A LQG-based load frequency controller in a competitive electricity environment. Int J Emerg Electr Power Syst 2005; 2: 1-13.
  • [12] Dola GP, Somanath M. A new control scheme for PID controller of single-area and multi-area power systems. ISA T 2013; 52: 242-251.
  • [13] Zamani AA, Bijami E, Sheikholeslam F, Jafrasteh B. Optimal fuzzy load frequency controller with simultaneous auto-tuned membership functions and fuzzy control rules. Turk J Elec Eng & Comp Sci 2014; 22: 66-86.
  • [14] Demiroren A, Zeynelgil HL. GA application to optimization of AGC in three-area power system after deregulation. Int J Elec Power 2007; 29: 230-240.
  • [15] Bhatt P, Roy R, Ghoshal SP. Optimized multi area AGC simulation in restructured power systems. Int J Elec Power 2010; 32: 311-332.
  • [16] Kumar N, Kumar V, Tyagi B. Optimization of PID parameters using BBBC for a multiarea AGC scheme in a deregulated power system. Turk J Elec Eng & Comp Sci 2016; 24: 4105-4116.
  • [17] Kumar N, Kumar V, Tyagi B. Deregulated multiarea AGC scheme using BBBC-FOPID controller. Arab J Sci Eng 2016; 42: 2641-2649.
  • [18] Fathima AP, Khan MA. Design of new market structure and robust controller for the frequency regulation service in the deregulated power system. Electr Pow Compo Sys 2008; 33: 864-883.
  • [19] Weber AZ, Matthew MM, Jeremy PM, Philip NR, Jeffery T, Gostick QL. Redox ow batteries. J Appl Electrochem 2011; 41: 1137-1164.
  • [20] Yang XS. Engineering Optimization: An Introduction with Metaheuristic Applications. New York, NY, USA: Wiley, 2010.
  • [21] Magid YLA, Dawoud MM. Optimal AGC tuning with genetic algorithms. Electr Pow Syst Res 1996; 38: 231-238.
  • [22] Kennedy J, Eberhart R. Swarm Intelligence. San Diego, CA, USA: Academic Press, 2001.
  • [23] Glover BJ. Understanding Flowers and Flowering: An Integrated Approach. Oxford, UK: Oxford University Press, 2007.
  • [24] Yang XS. Engineering Optimization: An Introduction with Metaheuristic Application. New York, NY, USA: Wiley, 2010.
Turkish Journal of Electrical Engineering and Computer Sciences-Cover
  • ISSN: 1300-0632
  • Yayın Aralığı: Yılda 6 Sayı
  • Yayıncı: TÜBİTAK