Transient Analysis of Quasi Oppositional Based Lightning Search Algorithm Optimized PID Controller in Isolated Small Hydro Power Plant
Abstract
In this paper, Small Hydro Plant (SHP) of 1.3 MW is simulated with two conventional PID controllers in excitation system and governor to enhance the capability to handle the transiency of the generator. Excitation voltage control and turbine speed control are the two basic control schemes, to regulate reactive power or terminal voltage and real power or frequency respectively. The selection parameters of the PID controllers are significant to enhance the performance of the system. Quasi Oppositional BaseÂÂd Lightning Search Algorithm (QOLSA) is validated in this paper to optimize the PID controllers over LSA and PSO. Renewable energy source like SHP is environment friendly and very imperative to meet the vigorously growing load demand. The simulation of the SHP is established in MATLAB/SIMULINK environment. Finally, QOLSA optimized PID controller contributes better control in terminal voltage and power over LSA and PSO algorithms. Â
Citation:Â Kaushaley, S., and Shaw, B. (2018). Transient Analysis of Quasi Oppositional Based Lightning Search Algorithm Optimized PID Controller in Isolated Small Hydro Power Plant. Trends in Renewable Energy, 4, 34-43. DOI: 10.17737/tre.2018.4.3.0048
Keywords
Full Text:
FULL TEXT (PDF)References
G. Baidya, “Development of Small Hydro,†Himal. Small Hydropower Summit, pp. 34–43, 2006. http://ahec.org.in/links/HSHS/Presentations/Links/Technical%20Papers/Overview%20of%20SHP%20Development/Mr%20G%20Baidya_Development%20of%20SH.pdf (accessed on 4/26/2018)
L. N. Hannett, J. W. Feltes, and B. Fardanesh, “Field test to validate hydro-turbine governor model structure and parameters,†IEEE Trans. Power Syst., vol. 9, no. 4, pp. 1744–1751, 1994.
N. K. Dewangan, H. S. Sachdev, and B. Shaw, “An Analysis of Transient Response of Isolated Small Hydropower Plant with Application of CRPSO Optimized PID Controller,†International Journal of Pure and Applied Mathematics, vol. 114, no. 9, pp. 137–145, 2017.
L. A. L. Tenorio, “Hydro Turbine and Governor Modelling: Electric - Hydraulic Interaction,†Norwegian University of Science and Technology, Master Thesis, 2010. https://daim.idi.ntnu.no/masteroppgaver/005/5451/masteroppgave.pdf (accessed on 4/26/2018)
P. Kundur, N.J. Balu, and M.G. Lauby, Power system stability and control. Vol. 7. 1994: McGraw-hill New York.
K. Kim and R. C. Schaefer, “Tuning a PID controller for a digital excitation control system,†Conf. Rec. 2004 Annu. Pulp Pap. Ind. Tech. Conf. (IEEE Cat. No.04CH37523), vol. 41, no. 2, pp. 485–492, 2004.
F. P. De Melo and R. J. Koessler, “Hydraulic Turbine and Turbine Control Models for System Dynamic Studies,†Trans. Power Syst., vol. 7, no. 1, pp. 167–179, 1992.
S. Syan and G. R. Biswal, “Frequency control of an isolated hydro power plant using artificial intelligence,†2015 IEEE Work. Comput. Intell. Theor. Appl. Futur. Dir., pp. 1–5, 2015. DOI: 10.1109/WCI.2015.7495537
H. Goyal, T. S. Bhatti, and D. P. Kothari, “A novel technique proposed for automatic control of small hydro power plants,†International Journal of Global Energy Issues, vol. 24, pp. 29-46, 2005. DOI: 10.1504/IJGEI.2005.007076
M. G. Molina and M. Pacas, “Improved power conditioning system of micro-hydro power plant for distributed generation applications,†2010 IEEE Int. Conf. Ind. Technol., pp. 1733–1738, 2010. DOI: 10.1109/ICIT.2010.5472461
G. A. Aggidis, E. Luchinskaya, R. Rothschild, and D. C. Howard, “The costs of small-scale hydro power production: Impact on the development of existing potential,†Renew. Energy, vol. 35, no. 12, pp. 2632–2638, 2010
R. Bhoi and D. S. M. Ali, “Potential of Hydro Power Plant in India and its Impact on Environment,†Int. J. Eng. Trends Technol., vol. 10, no. 3, pp. 114–119, 2014.
T. Abbasi and S. A. Abbasi, “Small hydro and the environmental implications of its extensive utilization,†Renew. Sustain. Energy Rev., vol. 15, no. 4, pp. 2134–2143, 2011.
J. R. Nayak, B. Shaw, and B. K. Shahu, “Load frequency control of hydro-thermal power system using fuzzy PID controller optimized by hybrid DECRPSO algorithm,†International Journal of Pure and Applied Mathematics, vol. 114, no. 9, pp. 147–155, 2017.
H. Shareef, A. A. Ibrahim, and A. H. Mutlag, “Lightning search algorithm,†Appl. Soft Comput. J., vol. 36, pp. 315–333, 2015.
N. I. Petrov, G. N. Petrova, and F. D. Alessandro, “Quantification of the Probability of Lightning Strikes to Structures Using a Fractal Approach,†IEEE Transactions on Dielectrics and Electrical Insulation, vol. 10, no. 4, pp. 641–654, 2003. DOI: 10.1109/TDEI.2003.1219649
H. R. Tizhoosh, “Opposition-Based Learning: A New Scheme for Machine Intelligence,†Comput. Intell. Model. Control Autom. 2005 Int. Conf. Intell. Agents, Web Technol. Internet Commer. Int. Conf., vol. 1, pp. 695–701, 2005.
C. K. Shiva and V. Mukherjee, “A novel quasi-oppositional harmony search algorithm for AGC optimization of three-area multi-unit power system after deregulation,†Eng. Sci. Technol. an Int. J., vol. 19, no. 1, pp. 395–420, 2016.
J. R. Nayak, B. Shaw, and B. K. Sahu, “Application of adaptive-SOS (ASOS) algorithm based interval type-2 fuzzy-PID controller with derivative filter for automatic generation control of an interconnected power system,†Int. J. Engineering Science and Technology, 2018. DOI: 10.1016/j.jestch.2018.03.010.
J.R. Nayak, B. Shaw, S. Das, and B.K. Sahu, “Design of MI fuzzy PID controller optimized by Modified Group Hunting Search algorithm for interconnected power system,†Microsyst. Technol., 2018. DOI: 10.1007/s00542-018-3788-3.
DOI: http://dx.doi.org/10.17737/tre.2018.4.3.0048
Refbacks
- There are currently no refbacks.
Copyright (c) 2018 Shashikant Kaushaley and Binod Shaw
This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 License.
Copyright @2014-2025 Trends in Renewable Energy (ISSN: 2376-2136, online ISSN: 2376-2144)