LOAD-FREQUENCY OPTIMIZATION WITH HEURISTIC TECHNIQUES IN A AUTONOMOUS HYBRID AC MICROGRID

Year 2017, Volume: 2 Issue: 1, 2 - 16, 30.06.2017

Dursun Öztürk , Hakan Çelik , Mahmut Temel Özdemir

https://doi.org/10.23884/IJESG.2017.2.1.01

Cited By: 2

Abstract

The
main problem that arises during the operation of all these power systems is
load-frequency control. Load-frequency control is a common problem of power
systems that are connected to an interconnected system. Variations in the
frequency in the interconnected power systems can lead to large-scale and
serious instability problems. And in microgrids, load-frequency control is of
great importance in order to provide active power balancing, especially when
the microgrids are connected to the main grid. In this study, AC microgrid
structures and their basic control cycles are examined. A sample autonomous
hybrid AC microgrid structure was modeled in the MATLAB environment and an autonomous
hybrid AC microgrid system isolated from the main grid was considered to be the
case study. In this case, the controller gains are determined according to the
Optic Inspired Optimization, Bacterial Swarm Optimization, Artificial Bee
Colony Optimization, Ant Colony Optimization, Grey Wolf Colony Optimization
algorithms, costing with the ISE performance criteria which are commonly
recognized in the literature. The controller gains determined by optimization
were simulated for time domain responses in the generated model and the results
were analyzed.    

Keywords

Autonomous hybrid ac microgrid, load-frequency control, optics inspired optimization, bacterial swarm optimization, artificial bee colony optimization, ant colony optimization, grey wolf colony optimization

References

• El-Khattam, W., et al., Distributed generation technologies, definitions and benefits 2004, 71, pp. 119–128
• Doolla, S., et al., Automatic generation control of an isolated small-hydro power plant. Electric Power Systems Research, 76, (2006), 9–10, pp. 889–896.
• Banerjee, A., et al., Intelligent fuzzy-based reactive power compensation of an isolated hybrid power system. International Journal of Electrical Power and Energy Systems, 57, (2014), pp. 164–177.
• Aghamohammadi, M.R., et al., A new approach for optimal sizing of battery energy storage system for primary frequency control of islanded Microgrid. International Journal of Electrical Power & Energy Systems, 54, (2014), pp. 325–333.
• Barsali, S., et al., Storage applications for Smartgrids. Electric Power Systems Research, 120, (2015), pp. 109–117.
• Hien, N.C., et al., Location and Sizing of Distributed Generation Units for Loadabilty Enhancement in Primary Feeder. IEEE Systems Journal, 7, (2013), 4, pp. 797–806.
• Lopes, J.A.P., et al., Integrating distributed generation into electric power systems: A review of drivers, challenges and opportunities. Electric Power Systems Research, 77, (2007), 9, pp. 1189–1203.
• Sebastián, R., et al., Control and simulation of a flywheel energy storage for a wind diesel power system. International Journal of Electrical Power & Energy Systems, 64, (2015), pp. 1049–1056.
• Zhao, J.H., et al., Flexible transmission network planning considering distributed generation impacts. IEEE Transactions on Power Systems, 26, (2011), 3, pp. 1434–1443.
• Loh, P.C., et al., Autonomous control of interlinking converter with energy storage in hybrid AC-DC microgrid. IEEE Transactions on Industry Applications, 49, (2013), 3, pp. 1374–1382.
• Cohn, N., Considerations in the Regulation of Interconnected Areas. IEEE Transactions on Power Apparatus and Systems, PAS-86, (1967), 12, pp. 1527–1538.
• Hatziargyriou, N., et al., Microgrids 2007, 5, pp. 78–94
• Lee, D.-J., et al., Small-Signal Stability Analysis of an Autonomous Hybrid Renewable Energy Power Generation/Energy Storage System Part I: Time-Domain Simulations. IEEE Transactions on Energy Conversion, 23, (2008), 1, pp. 311–320.
• Das, D.C., et al., GA based frequency controller for solar thermal–diesel–wind hybrid energy generation/energy storage system. International Journal of Electrical Power & Energy Systems, 43, (2012), 1, pp. 262–279.
• Wang, L., et al., Analysis of a novel autonomous marine hybrid power generation/energy storage system with a high-voltage direct current link. Journal of Power Sources, 185, (2008), 2, pp. 1284–1292.
• Senjyu, T., et al., A Hybrid Power System Using Alternative Energy Facilities in Isolated Island. IEEE Transactions on Energy Conversion, 20, (2005), 2, pp. 406–414.
• Gao, L., et al., Power Enhancement of an Actively Controlled Battery/Ultracapacitor Hybrid. IEEE Transactions on Power Electronics, 20, (2005), 1, pp. 236–243.
• Aditya, S.K., et al., Application of battery energy storage system to load frequency control of an isolated power system. International Journal of Energy Research, 23, (1999), 3, pp. 247–258.
• Kottick, D., et al., Battery Energy Storage for Frequency Regulation in an Island Power System. IEEE Transactions on Energy Conversion, 8, (1993), 3, pp. 455–459.
• Ray, P., et al., Small-Signal Analysis of Autonomous Hybrid Distributed Generation Systems in Presence of Ultracapacitor and Tie-Line Operation. Journal of Electrical Engineering, 61, (2010), 4.
• Özdemir, M.T., et al., Tuning of Optimal Classical and Fractional Order PID Parameters for Automatic Generation Control Based on the Bacterial Swarm Optimization. In: IFAC-PapersOnLine. 2015, pp. 501–506.
• Koç, F., et al., The Effect of Derivative Gain to System Stability in Automatic Voltage Regulator Systems. In: International Engineering, Science and Education Conference (INESEC) (Editors: B. Gümüş et al.). Diyarbakır, 2016, pp. 829–836.
• Özdemir, M.T., et al., An experimental system for electrical and mechanical education: Micro hydro power plant prototype. Procedia-Social and Behavioral Sciences, 47, (2012), pp. 2114–2119.
• Özdemir, M.T., et al., Effects of High Voltage Direct Current Transmission Lines on Load Frequency Control in a Multi Area Power System. In: Güç Sistemleri Konferansı 2016. 2016, pp. 1–5.
• Nur, A., et al., Power Flow Study For a Microgrid By Using Matlab And Powerworld SimulatorSIMULATOR. International Journal of Energy and Smart Grid, 1, (2016), 1, pp. 14–21.
• Efe, S.B., Power Flow Analysis of A Distribution System Under Fault Conditions. International Journal of Energy and Smart Grid, 1, (2016), 1, pp. 22–27.
• Çelik, V., et al., The effects on stability region of the fractional-order PI controller for one-area time-delayed load--frequency control systems. Transactions of the Institute of Measurement and Control, (2016), pp. 142331216642839.
• Özdemir, M.T., et al., Load-Frequency Optimization with Heuristic Techniques in A Hybrid AC Microgrid. In: International Engineering, Science and Education Conference (INESEC). 2016, pp. 837–845.
• Shankar, G., et al., Load frequency control of an autonomous hybrid power system by quasi-oppositional harmony search algorithm. International Journal of Electrical Power & Energy Systems, 78, (2016), pp. 715–734.
• Akyol, S., et al., Güncel Sürü Zekası Optamizasyon Algoritmaları. Nevşehir Bilim ve Teknoloji Dergisi, 1, (2012), 1.
• Karaboga, D., et al., A comparative study of Artificial Bee Colony algorithm. Applied Mathematics and Computation, 214, (2009), 1, pp. 108–132.
• Zhu, G., et al., Gbest-guided artificial bee colony algorithm for numerical function optimization. Applied Mathematics and Computation, 217, (2010), 7, pp. 3166–3173.
• Li, G., et al., Development and investigation of efficient artificial bee colony algorithm for numerical function optimization. Applied Soft Computing, 12, (2012), 1, pp. 320–332.
• Eke, İ., et al., Yapay Arı Kolonisi Algoritması Tabanlı Kararlı Güç Sistemi Dengeleyicisi Tasarımı. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 26, (2011), 3.
• Korani, W.M., et al., Bacterial Foraging Oriented by Particle Swarm Optimization Strategy for PID Tuning. Ieee International Symposium on Computational Intelligence in Robotics and Automation, (2009), pp. 445–450.
• Ali, E.S., et al., Bacteria foraging optimization algorithm based load frequency controller for interconnected power system. International Journal of Electrical Power & Energy Systems, 33, (2011), 3, pp. 633–638.
• Saikia, L.C., et al., Automatic generation control of a multi area hydrothermal system using reinforced learning neural network controller. International Journal of Electrical Power and Energy Systems, 33, (2011), 4, pp. 1101–1108.
• Dorigo, M., et al., The ant system: An autocatalytic optimizing process. TR91-016, Politecnico di Milano, (1991), pp. 1–21.
• Öztürk, D., et al., Calculation of surface leakage currents on high voltage insulators by ant colony algorithm-supported FEM. TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 23, (2015), pp. 1009–1024.
• Mirjalili, S., et al., Grey Wolf Optimizer. Advances in Engineering Software, 69, (2014), pp. 46–61.
• Vila, C., et al., Mitochondrial DNA phylogeography and population history of the grey wolf Canis lupus. Molecular Ecology, 8, (1999), pp. 2089–2103.
• Özdemir, M.T., et al., Optimal Load frequency control in two area power systems with Optics Inspired Optimization. Firat Universitesi Muhendislik Bilimleri Dergisi, 2, (2016), 28, pp. 57–66.
• Husseinzadeh Kashan, A., A new metaheuristic for optimization: Optics inspired optimization (OIO). Computers and Operations Research, 55, (2014), pp. 99–125.