Optimal design of PD-Fuzzy-PID cascaded controller for automatic generation control

References

• Alomoush, M. I. (2010). Load frequency control and automatic generation control using fractional-order controllers. Electrical Engineering, 91(7), 357–368.10.1007/s00202-009-0145-7
   Web of Science ®Google Scholar
• Arya, Y. (2017). AGC performance enrichment of multi-source hydrothermal gas power systems using new optimized FOFPID controller and redox flow batteries. Energy, 127, 704–715.10.1016/j.energy.2017.03.129
   Web of Science ®Google Scholar
• Arya, Y., & Kumar, N. (2016a). Optimal AGC with redox flow batteries in multi-area restructured power systems. Engineering Science and Technology, an International Journal, 19(3), 1145–1159.10.1016/j.jestch.2015.12.014
   Google Scholar
• Arya, Y., & Kumar, N. (2016b). AGC of a multi-area multi-source hydrothermal power system interconnected via AC/DC parallel links under deregulated environment. International Journal of Electrical Power & Energy Systems, 75, 127–138.10.1016/j.ijepes.2015.08.015
   Web of Science ®Google Scholar
• Arya, Y., & Kumar, N. (2016c). Fuzzy gain scheduling controllers for AGC of two-area interconnected electrical power systems. Electric Power Components and Systems, 44(7), 737–751.10.1080/15325008.2015.1131765
   Web of Science ®Google Scholar
• Cohn, N. (1956). Some aspects of tie-line bias control on interconnected power systems. IEEE Transactions on Power Apparatus and Systems, 1956, 1415–1436.
   Google Scholar
• El-Hameed, M. A., & El-Fergany, A. A. (2016). Water cycle algorithm-based load frequency controller for interconnected power systems comprising non-linearity. IET Generation, Transmission & Distribution, 10(15), 3950–3961.10.1049/iet-gtd.2016.0699
   Web of Science ®Google Scholar
• Ghoshal, S. P. (2004). Optimizations of PID gains by particle swarm optimizations in fuzzy based automatic generation control. Electric Power Systems Research, 72(3), 203–212.10.1016/j.epsr.2004.04.004
   Web of Science ®Google Scholar
• Ghoshal, S. P., & Goswami, S. K. (2003). Application of GA based optimal integral gains in fuzzy based active power-frequency control of non-reheat and reheat thermal generating systems. Electric Power Systems Research, 67(2), 79–88.10.1016/S0378-7796(03)00087-7
   Web of Science ®Google Scholar
• Guha, D., Roy, P. K., & Banerjee, S. (2016). Load frequency control of interconnected power system using grey wolf optimization. Swarm and Evolutionary Computation, 27, 97–115.
   Web of Science ®Google Scholar
• Ismayil, C., Kumar, R. S., & Sindhu, T. K. (2015). Optimal fractional order PID controller for automatic generation control of two-area power systems. International Transactions on Electrical Energy Systems, 25(12), 3329–3348.
   Web of Science ®Google Scholar
• Khuntia, S. R., & Panda, S. (2012). Simulation study for automatic generation control of a multi-area power system by ANFIS approach. Applied Soft Computing, 12(1), 333–341.10.1016/j.asoc.2011.08.039
   Web of Science ®Google Scholar
• Kothari, M. L., & Nanda, J. (1988). Application of optimal control strategy to automatic generation control of a hydrothermal system. IEE Proceedings D Control Theory and Applications, 135(4), 268–274.10.1049/ip-d.1988.0037
   Google Scholar
• Kundur, P. (1994). Power system stability and control. New York, NY: McGraw-Hill.
   Google Scholar
• Lal, Deepak Kumar, & Barisal, A. K. (2017). Comparative performances evaluation of FACTS devices on AGC with diverse sources of energy generation and SMES. Cogent Engineering, 4(1), 1318466.
   Web of Science ®Google Scholar
• Manoj Kumar Debnath, R. K., Mallick, S. D., & Aman, A. (2016). Gravitational search algorithm (GSA) optimized fuzzy-PID controller design for load frequency control of an interconnected multi-area power system. 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT), IEEE.
   Google Scholar
• Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey wolf optimizer. Advances in Engineering Software, 69, 46–61.10.1016/j.advengsoft.2013.12.007
   Web of Science ®Google Scholar
• Mohanty, B., Panda, S., & Hota, P. K. (2014a). Differential evolution algorithm based automatic generation control for interconnected power systems with non-linearity. Alexandria Engineering Journal, 53(3), 537–552.10.1016/j.aej.2014.06.006
   Google Scholar
• Mohanty, B., Panda, S., & Hota, P. K. (2014b). Controller parameters tuning of differential evolution algorithm and its application to load frequency control of multi-source power system. International Journal of Electrical Power & Energy Systems, 54, 77–85.10.1016/j.ijepes.2013.06.029
   Web of Science ®Google Scholar
• Mudi, K. R., & Pal, R. N. (1999). A robust self-tuning scheme for PI-and PD-type fuzzy controllers. IEEE Transactions on Fuzzy Systems, 7(1), 2–16.10.1109/91.746295
   Web of Science ®Google Scholar
• Nanda, J., Mangla, A., & Suri, S. (2006). Some new findings on automatic generation control of an interconnected hydrothermal system with conventional controllers. IEEE Transactions on Energy Conversion, 21(1), 187–194.10.1109/TEC.2005.853757
   Web of Science ®Google Scholar
• Nanda, J., Mishra, S., & Saikia, L. C. (2009). Maiden application of bacterial foraging-based optimization technique in multiarea automatic generation control. IEEE Transactions on Power Systems, 24(2), 602–609.10.1109/TPWRS.2009.2016588
   Web of Science ®Google Scholar
• Nanda, J., & Saikia, L. C. (2008). Comparison of performances of several types of classical controller in automatic generation control for an interconnected multi-area thermal system. Power Engineering Conference, 2008. AUPEC’08, Australasian Universities. IEEE.
   Google Scholar
• Ou, T.-C. (2012). A novel unsymmetrical faults analysis for microgrid distribution systems. International Journal of Electrical Power & Energy Systems, 43(1), 1017–1024.10.1016/j.ijepes.2012.05.012
   Web of Science ®Google Scholar
• Ou, T.-C. (2013). Ground fault current analysis with a direct building algorithm for microgrid distribution. International Journal of Electrical Power & Energy Systems, 53, 867–875.10.1016/j.ijepes.2013.06.005
   Web of Science ®Google Scholar
• Ou, T.-C., & Hong, C.-M. (2014). Dynamic operation and control of microgrid hybrid power systems. Energy, 66, 314–323.10.1016/j.energy.2014.01.042
   Web of Science ®Google Scholar
• Ou, T.-C., Lu, K.-H., & Huang, C.-J. (2017). Improvement of transient stability in a hybrid power multi-system using a designed NIDC (Novel Intelligent Damping Controller). Energies, 10(4), 488.10.3390/en10040488
   Web of Science ®Google Scholar
• Padhy, S., Panda, S., & Mahapatra, S. (2017). A modified GWO technique based cascade PI-PD controller for AGC of power systems in presence of Plug in Electric Vehicles. Engineering Science and Technology, an International Journal, 20(2), 427–442.10.1016/j.jestch.2017.03.004
   Google Scholar
• Sahu, B. K., Pati, S., & Panda, S. (2014). Hybrid differential evolution particle swarm optimization optimized fuzzy proportional–integral derivative controller for automatic generation control of interconnected power system. IET Generation, Transmission & Distribution, 8(11), 1789–1800.10.1049/iet-gtd.2014.0097
   Web of Science ®Google Scholar
• Pradhan, P. C., Sahu, R. K., & Panda, S. (2016). Firefly algorithm optimized fuzzy PID controller for AGC of multi-area multi-source power systems with UPFC and SMES. Engineering Science and Technology, an International Journal, 19(1), 338–354.
   Google Scholar
• Rao, R. V., Savsani, V. J., & Vakharia, D. P. (2012). Teaching–learning-based optimization: An optimization method for continuous non-linear large scale problems. Information Sciences, 183(1), 1–15.10.1016/j.ins.2011.08.006
   Web of Science ®Google Scholar
• Rout, U. K., Sahu, R. K., & Panda, S. (2013). Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system. Ain Shams Engineering Journal, 4(3), 409–421.10.1016/j.asej.2012.10.010
   Google Scholar
• Sahu, R. K., Panda, S., & Padhan, S. (2014). Optimal gravitational search algorithm for automatic generation control of interconnected power systems. Ain Shams Engineering Journal, 5(3), 721–733.
   Google Scholar
• Sahu, R. K., Gorripotu, T. S., & Panda, S. (2016). Automatic generation control of multi-area power systems with diverse energy sources using teaching learning based optimization algorithm. Engineering Science and Technology, an International Journal, 19(1), 113–134.
   Google Scholar
• Sahu, B. K., Pati, T. K., Nayak, J. R., Panda, S., & Kar, S. K. (2016). A novel hybrid LUS–TLBO optimized fuzzy-PID controller for load frequency control of multi-source power system. International Journal of Electrical Power & Energy Systems, 74, 58–69.10.1016/j.ijepes.2015.07.020
   Web of Science ®Google Scholar
• Shabani, H., Vahidi, B., & Ebrahimpour, M. (2013). A robust PID controller based on imperialist competitive algorithm for load-frequency control of power systems. ISA Transactions, 52(1), 88–95.10.1016/j.isatra.2012.09.008
   PubMed Web of Science ®Google Scholar
• Singh, O., & Nasiruddin, I. (2016). Optimal AGC regulator for multi-area interconnected power systems with parallel AC/DC links. Cogent Engineering, 3(1), 1209272.
   Web of Science ®Google Scholar
• Singh, O., & Nasiruddin, I. (2016). Hybrid evolutionary algorithm based fuzzy logic controller for automatic generation control of power systems with governor dead band non-linearity. Cogent Engineering, 3(1), 1161286.
   Web of Science ®Google Scholar
• Wang, Y., Zhou, R., & Wen, C. (1994). New robust adaptive load-frequency control with system parametric uncertainties. IEE Proceedings-Generation, Transmission and Distribution, 141(3), 184–190.10.1049/ip-gtd:19949757
   Google Scholar
• Yousef, H. A., et al. (2014). Load frequency control of a multi-area power system: An adaptive fuzzy logic approach. IEEE Transactions on Power Systems, 29(4), 1822–1830.10.1109/TPWRS.2013.2297432
   Web of Science ®Google Scholar