System Dynamics and Frequency Regulation of a Multi-Area Power System Using an Optimal Controller
Keywords:
Power system, Optimal Controller, Thermal solar, Thermal windAbstract
For system frequency control, the current work proposes a multi-area power system integrating various renewable sources. An effective controller with intrinsic superior capabilities of restricting peak deviation, steady state errors, and oscillatory behavior of a dynamic system is an apparent alternative for autonomous generation control of interconnected power systems. The most difficult part of using a controller is figuring out how to get the most out of it. Because of its space complexity, the trial and error method of determining the benefit by indirect optimization with an acceptable performance index appears to be insufficient. As a result, it appears that using an effective algorithm technique to find the maximum gains for the controllers is the best option. The gains of the controllers are addressed in this work and thus are optimized using a meta-heuristic technique in this study.
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Janardan Nanda, S. Mishra, & Lalit Chandra Saika. Maiden application of bacterial foraging-based optimization technique in multiarea automatic generation control, IEEE Transactions on Power Systems, vol.24, no.6, pp.602-609, 2009.
Praghnesh Bhatt, Ranjit Roy, & S.P. Ghoshal. Comparative performance evaluation of SMES SMES, TCPS-SMES, & SSSC-SMES controllers in automatic generation control for a two-area hydro hydro system, International Journal of Electrical Power & Energy Systems, vol.33, no.1, pp. 1585- 1597,2011.
Electric Energy Systems Theory, ElgerdOl. New Delhi, Tata McGraw-Hill,2007. An introduction. 2nd edition.
Kandur, P. (2009) Power System Stability & Control, 8th reprint, Tata McGraw-Hill, New Delhi.
Bevrani H. Robust power system frequency control. New York, Springer; 2009.
Pappachen, A., Fathima, A. P.,2017. Critical research areas on load frequency control issues in a deregulated power system: A state-of-the-art-of review, Renewable and Sustainable Energy Reviews, Elsevier, vol.72, pp. 163-177.D
NERC’S Balancing and Frequency Control, subcommittee, NERC, Princeton,2011.
Electric Energy Systems Theory, ElgerdOl. New Delhi, Tata McGraw-Hill,2007. An introduction. 2nd edition.
J. Nanda, A. Mangla, S. Suri. Some new findings on automatic generation control of an interconnected hydrothermal system with conventional controllers. 2006; 21:187-93 in IEEE Transactions on Energy Conversion.
K.P. Singh Parmar, S. Majhi, D.P. Kothari, Load frequency control of a realistic power system with multi-source power generation. 201; 42:426-33 in International journal of Electrical power and Energy systems.
SP Ghoshal. Fuzzy automatic generation control of a multi-area thermal generating system using GA/GA SA. Electric Power Systems Research, Elsevier, vol.70, no.1, pp115-27,2004.
HalukGozde, M. Cengiz Taplamacioglu. Automatic generation control application in a thermal power system using craziness-based particle swarm optimization, Elsevier, vol.33, pp.8-16 in International Journal of Electrical Power and Energy Systems.
Janardan Nanda, S. Mishra, & Lalit Chandra Saika. Maiden application of bacterial foraging-based optimization technique in multiarea automatic generation control, IEEE Transactions on Power Systems, vol.24, no.6, pp.602-609,2009.
Umesh Kumar Rout, Rabindra Kumar Sahu, &Sidhartha Panda, Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system, Elsevier, vol.4, pp.409-421,2012.
K.R.M. Vijaya Chandrakala, S. Balamurugan, K. Sankaranarayanan, Variable structure fuzzy gain scheduling-based load frequency controller for multi source multi area hydro thermal system, Elsevier, 53:375-381 in International Journal of Electrical Power and Energy Systems,2013.
Lalit Chandra Saika, Sukumar Mishra, Nidul Sinha & Janardan Nanda, Automatic generation control of a multi area hydrothermal system using reinforced learning neural network controller, Elsevier, 33:1101-1108 in International Journal of Electrical Power and Energy Systems,2011.
Xin-She Yang, Firefly Algorithms for Multimodal Optimization, Springer, Berlin, Heidelberg, pp. 169- 178 in Stochastic Algorithms,2009.
Xin-She Yang, Firefly Algorithm, Stochastic Test Functions and Design optimisation, Inderscience,Int. J. Bio-Inspired Computation, Vol. 2, No. 2, pp.78- 84,2010.
Saroj Padhan, Rabindra Kumar Sahu, &Sidhartha Panda, Applications of Firefly Algorithm for Load Frequency Control of Multi-area Interconnected Power System. Electric Power Components and Systems, Vol. 42, pp.1419-1430,2014.
J. Senthilnath, Omkar S N, V. Mani, Clustering Using Firefly Algorithm: Performance Study. Elsevier, 1:169-171,2011.
Liao K, Xu Y. A robust load frequency control scheme for power systems based on second order sliding mode and extended disturbance observer. IEEE Transactions on industrial informatics. 2017 Nov 9;14(7):3076-3086.